@@ -63,7 +63,7 @@
diff --git a/articles/download_functions.html b/articles/download_functions.html
index 0b92a970..829fe404 100644
--- a/articles/download_functions.html
+++ b/articles/download_functions.html
@@ -739,7 +739,7 @@
-
## Test passed 😸
+
## Test passed 🎉
As expected, the test passes because the NOAA HMS Smoke data set does
not contain data for January 1-2, 1800.
These unit tests are just two of many implemented on
@@ -1213,7 +1213,7 @@
diff --git a/pkgdown.yml b/pkgdown.yml
index 16e16cb6..013104b1 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -4,8 +4,8 @@ pkgdown_sha: ~
articles:
download_functions: download_functions.html
epa_download: epa_download.html
-last_built: 2024-03-08T14:18Z
+last_built: 2024-03-14T15:31Z
urls:
- reference: https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference
- article: https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles
+ reference: https://kyle-messier.github.io/amadeus/reference
+ article: https://kyle-messier.github.io/amadeus/articles
diff --git a/search.json b/search.json
index 8b09b0ad..4ca372d6 100644
--- a/search.json
+++ b/search.json
@@ -1 +1 @@
-[{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"motivation","dir":"Articles","previous_headings":"","what":"Motivation","title":"download_data() and NASA EarthData Account","text":"data_download() function developed improve researchers’ access publicly available geospatial data sets. Although data already available online, using web browser manually download hundreds thousands data files slow, arduous, (efficiently) repeatable. Additionally, users may familiar creating download recipes Bash (Unix shell), data_download() allows researchers download data directly R, common coding language field environmental health research. Finally, function-izing data downloads useful repeated code automated analysis pipelines.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"data_download","dir":"Articles","previous_headings":"","what":"data_download()","title":"download_data() and NASA EarthData Account","text":"data_download() capable accessing downloading geospatial data sets, collections, variables variety sources. wrapper function calls source-specific data download functions, utilizing unique combination input parameters, host URL, naming convention, data formats. Source-Specific Download Functions Sources important note data_download() calls source-specific function based dataset_name = parameter. Using source-specific function directly return exact data (parameters ), data_download() may beneficial using loop download data various sources. example, download_data(dataset_name = \"hms\", ...) return data download_hms_data(...) assuming ... indicates parameters.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"parameters","dir":"Articles","previous_headings":"data_download()","what":"Parameters","title":"download_data() and NASA EarthData Account","text":"User-defined parameters differ based data source. Required parameters source can checked names(formals()). two functions different required parameters download_hms_data() uses daily temporal resolution download_narr_monolevel_data() uses yearly, share common, standard parameters.","code":"names(formals(download_hms_data)) ## [1] \"date_start\" \"date_end\" ## [3] \"data_format\" \"directory_to_download\" ## [5] \"directory_to_save\" \"data_download_acknowledgement\" ## [7] \"download\" \"remove_command\" ## [9] \"unzip\" \"remove_zip\" names(formals(download_narr_monolevel_data)) ## [1] \"year_start\" \"year_end\" ## [3] \"variables\" \"directory_to_save\" ## [5] \"data_download_acknowledgement\" \"download\" ## [7] \"remove_command\""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"standard-parameters","dir":"Articles","previous_headings":"data_download() > Parameters","what":"Standard parameters","title":"download_data() and NASA EarthData Account","text":"Four parameters included data download functions. Additionally, dataset_name = parameter must specified using data_download(), assumed using source-specific download function.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"function-structure","dir":"Articles","previous_headings":"data_download()","what":"Function Structure","title":"download_data() and NASA EarthData Account","text":"Although source-specific download function unique, follow general structure. following chunks code adopted download_hms_data() demonstrate functions’ structure. 1. Clean Parameters 2. Generate Download URLs 3. Generate download file names 4. Initiate “…commands.txt” 5. Concatenate download commands 6. Finalize “…commands.txt” 7. Run commands “…commands.txt” 8. Zip files (applicable)","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"clean-parameters","dir":"Articles","previous_headings":"data_download() > Function Structure","what":"1. Clean parameters","title":"download_data() and NASA EarthData Account","text":"Cleaning user-defined parameters highly dependent parameters desired URL created. common parameter cleaning step creating date-time sequence based given temporal range required format, case YYYYMMDD.","code":"# user defined parameters date_start <- \"2023-12-28\" date_end <- \"2024-01-02\" date_sequence <- seq( as.Date(date_start, format = \"%Y-%m-%d\"), as.Date(date_end, format = \"%Y-%m-%d\"), \"day\" ) date_sequence <- gsub(\"-\", \"\", as.character(date_sequence)) date_sequence ## [1] \"20231228\" \"20231229\" \"20231230\" \"20231231\" \"20240101\" \"20240102\""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"generate-download-urls","dir":"Articles","previous_headings":"data_download() > Function Structure","what":"2. Generate download URLs","title":"download_data() and NASA EarthData Account","text":"URL base pattern identified manually inspecting download link source-specific web page. download_hms_data() utilizes year, month, date, data format generate download url. download URL created date date_sequence based fixed pattern.","code":"# user defined parameters data_format <- \"Shapefile\" suffix <- \".zip\" urls <- NULL for (d in seq_along(date_sequence)) { year <- substr(date_sequence[d], 1, 4) month <- substr(date_sequence[d], 5, 6) base <- \"https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/\" url <- paste0( base, data_format, \"/\", year, \"/\", month, \"/hms_smoke\", date_sequence[d], suffix ) urls <- c(urls, url) } urls ## [1] \"https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/2023/12/hms_smoke20231228.zip\" ## [2] \"https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/2023/12/hms_smoke20231229.zip\" ## [3] \"https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/2023/12/hms_smoke20231230.zip\" ## [4] \"https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/2023/12/hms_smoke20231231.zip\" ## [5] \"https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/2024/01/hms_smoke20240101.zip\" ## [6] \"https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/2024/01/hms_smoke20240102.zip\""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"generate-download-file-names","dir":"Articles","previous_headings":"data_download() > Function Structure","what":"3. Generate download file names","title":"download_data() and NASA EarthData Account","text":"generation download file names also follows fixed pattern, typically combination user-defined download directory, data set name, spatiotemporal characteristic, data type, , applicable, specific variable name. Unlike download URLs, download file names can defined way writer function, using previously defined characteristics useful identification. download URL created date date_sequence based fixed pattern.","code":"# user defined parameters directory_to_download <- \"./data/\" download_file_names <- NULL for (d in seq_along(date_sequence)) { download_file_name <- paste0( directory_to_download, \"hms_smoke_\", data_format, \"_\", date_sequence[d], suffix ) download_file_names <- c(download_file_names, download_file_name) } download_file_names ## [1] \"./data/hms_smoke_Shapefile_20231228.zip\" ## [2] \"./data/hms_smoke_Shapefile_20231229.zip\" ## [3] \"./data/hms_smoke_Shapefile_20231230.zip\" ## [4] \"./data/hms_smoke_Shapefile_20231231.zip\" ## [5] \"./data/hms_smoke_Shapefile_20240101.zip\" ## [6] \"./data/hms_smoke_Shapefile_20240102.zip\""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"initiate-commands-txt","dir":"Articles","previous_headings":"data_download() > Function Structure","what":"4. Initiate “…commands.txt”","title":"download_data() and NASA EarthData Account","text":"important aspect data download function sink()...cat()...sink() structure. Rather using utils::download.file() function, text file created store download commands generated URLs file names. structure utilized several reasons: Consistent structure source-specific download functions. download.file() function accept vectors URLs destination files downloading. additional loop download data increase function complexity may reduce performance. Writing commands Bash (Unix shell) script allows specific arguments flags. Storing download URLs without immediately running download allows unit testing URL checking (Unit Tests). text file containing download commands named based data set, temporal range, data transfer method. Create sink text file.","code":"commands_txt <- paste0( directory_to_download, \"hms_smoke_\", head(date_sequence, n = 1), \"_\", tail(date_sequence, n = 1), \"_curl_commands.txt\" ) sink(commands_txt)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"concatenate-download-commands","dir":"Articles","previous_headings":"data_download() > Function Structure","what":"5. Concatenate download commands","title":"download_data() and NASA EarthData Account","text":"Linux-based download commands written according data transfer method, download URL, download file name, additional arguments. additional arguments included, order, depend data transfer method URL type. information curl wget, two data transfer methods utilized data download functions, see curl.1 man page GNU Wget 1.21.1-dirty Manual (latest version January 8, 2024). cat() function store download commands written loop previously sunk commands text file (commands_txt).","code":"for (d in seq_along(date_sequence)) { download_comamnd <- paste0( \"curl -s -o \", download_file_names[d], \" --url \", urls[d], \"\\n\" ) cat(download_comamnd) }"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"finalize-commands-txt","dir":"Articles","previous_headings":"data_download() > Function Structure","what":"6. Finalize “…commands.txt”","title":"download_data() and NASA EarthData Account","text":"download commands concatenated commands text file, second sink() command run finalize file stop appending R output.","code":"sink()"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"run-commands-in-commands-txt","dir":"Articles","previous_headings":"data_download() > Function Structure","what":"7. Run commands in “…commands.txt”","title":"download_data() and NASA EarthData Account","text":"“system command” must created run download commands stored commands text file. bash script, . indicates run commands within given script. case, run commands within commands text file. Running system_command deploys “helper function”, download_run(), function created reduce repeated code across source-specific download functions. function takes two parameters, system_command =, indicates command run, download =, user-defined logical parameter. data download initiated running download_run() system command identified download = TRUE. Checking download directory shows requested files downloaded.","code":"system_command <- paste0( \". \", commands_txt, \"\\n\" ) system_command ## [1] \". ./data/hms_smoke_20231228_20240102_curl_commands.txt\\n\" download_run <- function( download = FALSE, system_command = NULL) { if (download == TRUE) { cat(paste0(\"Downloading requested files...\\n\")) system(command = system_command) cat(paste0(\"Requested files have been downloaded.\\n\")) } else { cat(paste0(\"Skipping data download.\\n\")) return(NULL) } } download_run( download = TRUE, system_command = system_command ) list.files(path = directory_to_download) ## [1] \"hms_smoke_Shapefile_20231228.zip\" \"hms_smoke_Shapefile_20231229.zip\" ## [3] \"hms_smoke_Shapefile_20231230.zip\" \"hms_smoke_Shapefile_20231231.zip\" ## [5] \"hms_smoke_Shapefile_20240101.zip\" \"hms_smoke_Shapefile_20240102.zip\""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"zip-files-if-applicable","dir":"Articles","previous_headings":"data_download() > Function Structure","what":"8. Zip files (if applicable)","title":"download_data() and NASA EarthData Account","text":"source-specific data download functions follow general pattern, functions download zip files require additional steps inflate remove downloaded zip files, desired. two steps run helper functions, run user-defined unzip = remove_zip = parameters data_download(). download_unzip() inflates zip files unzip = TRUE, skips inflation unzip = FALSE. download_remove_zips() removes downloaded zip files remove = TRUE, skips removal remove = FALSE. demonstration unzip (inflate) downloaded zip files delete . Listing files shows contents zip files inflated zip files retained. download function structured successfully.","code":"download_unzip <- function(file_name, directory_to_unzip, unzip = TRUE) { if (!unzip) { cat(paste0(\"Downloaded files will not be unzipped.\\n\")) return(NULL) } cat(paste0(\"Unzipping files...\\n\")) unzip(file_name, exdir = directory_to_unzip ) cat(paste0( \"Files unzipped and saved in \", directory_to_unzip, \".\\n\" )) } download_remove_zips <- function(remove = FALSE, download_name) { if (remove) { cat(paste0(\"Removing download files...\\n\")) file.remove(download_name) cat(paste0(\"Download files removed.\\n\")) } } for (f in seq_along(download_file_names)) { download_unzip( file_name = download_file_names[f], directory_to_unzip = directory_to_download, unzip = TRUE ) } download_remove_zips( download_name = download_file_names, remove = FALSE ) ## Unzipping files... ## Files unzipped and saved in ./data/. ## Unzipping files... ## Files unzipped and saved in ./data/. ## Unzipping files... ## Files unzipped and saved in ./data/. ## Unzipping files... ## Files unzipped and saved in ./data/. ## Unzipping files... ## Files unzipped and saved in ./data/. ## Unzipping files... ## Files unzipped and saved in ./data/. list.files(path = directory_to_download) ## [1] \"hms_smoke_Shapefile_20231228.zip\" \"hms_smoke_Shapefile_20231229.zip\" ## [3] \"hms_smoke_Shapefile_20231230.zip\" \"hms_smoke_Shapefile_20231231.zip\" ## [5] \"hms_smoke_Shapefile_20240101.zip\" \"hms_smoke_Shapefile_20240102.zip\" ## [7] \"hms_smoke20231228.dbf\" \"hms_smoke20231228.prj\" ## [9] \"hms_smoke20231228.shp\" \"hms_smoke20231228.shx\" ## [11] \"hms_smoke20231229.dbf\" \"hms_smoke20231229.prj\" ## [13] \"hms_smoke20231229.shp\" \"hms_smoke20231229.shx\" ## [15] \"hms_smoke20231230.dbf\" \"hms_smoke20231230.prj\" ## [17] \"hms_smoke20231230.shp\" \"hms_smoke20231230.shx\" ## [19] \"hms_smoke20231231.dbf\" \"hms_smoke20231231.prj\" ## [21] \"hms_smoke20231231.shp\" \"hms_smoke20231231.shx\" ## [23] \"hms_smoke20240101.dbf\" \"hms_smoke20240101.prj\" ## [25] \"hms_smoke20240101.shp\" \"hms_smoke20240101.shx\" ## [27] \"hms_smoke20240102.dbf\" \"hms_smoke20240102.prj\" ## [29] \"hms_smoke20240102.shp\" \"hms_smoke20240102.shx\""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"unit-tests","dir":"Articles","previous_headings":"","what":"Unit Tests","title":"download_data() and NASA EarthData Account","text":"previous outline successfully cleaned parameters, generated URLs, downloaded data, can sure continue work different temporal ranges data types? end, unit tests implemented ensure data download function runs properly URLs produced 2. Generate download URLs valid accessible. Like download functions, unit tests rely “helper” functions reduce repeated code across tests.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"helper-functions","dir":"Articles","previous_headings":"Unit Tests","what":"Helper functions","title":"download_data() and NASA EarthData Account","text":"read_commands() imports commands text file converts data frame vector. extract_urls() extracts download URL vector commands. position = URL within download command determined 5. Concatenate download commands. check_url_status() important download test “helper” functions. function utilizes httr::HEAD() httr::GET() check HTTP response status given URL. desired HTTP response status 200, means URL valid accessible. check_url_status() returns logical value indicate whether URL returns HTTP status 200 (TRUE) (FALSE). information HTTP status’, see HTTP response status codes. check_urls() applies check_url_status() random sample URLs extracted extract_urls(). sample size vary based data set spatio-temporal parameters tested. function returns logical vector containing output check_url_status().","code":"read_commands <- function( commands_path = commands_path) { commands <- utils::read.csv(commands_path, header = FALSE) commands <- commands[seq_len(nrow(commands)), ] return(commands) } # function to extract URLs from vector extract_urls <- function( commands = commands, position = NULL) { if (is.null(position)) { cat(paste0(\"URL position in command is not defined.\\n\")) return(NULL) } url_list <- NULL for (c in seq_along(commands)) { url <- stringr::str_split_i(commands[c], \" \", position) url_list <- c(url_list, url) } return(url_list) } check_url_status <- function( url, method = \"HEAD\") { http_status_ok <- 200 if (method == \"HEAD\") { hd <- httr::HEAD(url) } else if (method == \"GET\") { hd <- httr::GET(url) } status <- hd$status_code return(status == http_status_ok) } check_urls <- function( urls = urls, size = NULL, method = \"HEAD\") { if (is.null(size)) { cat(paste0(\"URL sample size is not defined.\\n\")) return(NULL) } if (length(urls) < size) { size <- length(urls) } url_sample <- sample(urls, size, replace = FALSE) url_status <- sapply(url_sample, check_url_status, method = method ) return(url_status) }"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"testthat","dir":"Articles","previous_headings":"Unit Tests","what":"testthat","title":"download_data() and NASA EarthData Account","text":"demonstrate test action, test URLs generated download_data() NOAA HMS Smoke data set. information see testthat. Although testthat::test_that(...) chunk contains 32 lines code, unit test performed expect_true((url_status)). words, line expecting (expect_true()) (()) sampled URLs return HTTP response status 200 (url_status). Since expectation met, test passed! alternate example, can use start end date known data. URLs associated dates exist, expect function fail. test utilizes expect_error() data_download() wrapper function returns error message underlying source-specific download function returns error. test utilizes expect_error() data_download() wrapper function returns error message underlying source-specific download function returns error. directly used download_hms_data function, expect receive error. expected, test passes NOAA HMS Smoke data set contain data January 1-2, 1800. unit tests just two many implemented download_data() accompanying source-specific download functions, demonstrate unit testing helps build stable code.","code":"library(testthat) testthat::test_that( \"Valid dates return HTTP response status = 200.\", { # parameters test_start <- \"2023-12-28\" test_end <- \"2024-01-02\" test_directory <- \"./data\" # download download_data( dataset_name = \"noaa\", date_start = test_start, date_end = test_end, data_format = \"Shapefile\", directory_to_download = test_directory, directory_to_save = test_directory, data_download_acknowledgement = TRUE, download = FALSE, remove_command = FALSE, unzip = FALSE, remove_zip = FALSE ) commands_path <- paste0( test_directory, \"hms_smoke_\", gsub(\"-\", \"\", test_start), \"_\", gsub(\"-\", \"\", test_end), \"_curl_commands.txt\" ) # helpers commands <- read_commands(commands_path = commands_path) urls <- extract_urls(commands = commands, position = 6) url_status <- check_urls(urls = urls, size = 6, method = \"HEAD\") # test for true expect_true(all(url_status)) } ) ## Skipping data download. ## Downloaded files will not be unzipped. ## Downloaded files will not be unzipped. ## Downloaded files will not be unzipped. ## Downloaded files will not be unzipped. ## Downloaded files will not be unzipped. ## Downloaded files will not be unzipped. ## Test passed 🌈 testthat::test_that( \"Invalid dates cause function to fail.\", { # parameters test_start <- \"1800-01-01\" test_end <- \"1800-01-02\" test_directory <- \"../inst/extdata/\" # test for error testthat::expect_error( download_data( dataset_name = \"noaa\", date_start = test_start, date_end = test_end, data_format = \"Shapefile\", directory_to_download = test_directory, directory_to_save = test_directory, data_download_acknowledgement = TRUE, download = FALSE, remove_command = FALSE, unzip = FALSE, remove_zip = FALSE ) ) } ) ##
## function (date_start = \"2023-09-01\", date_end = \"2023-09-01\", ## data_format = \"Shapefile\", directory_to_download = NULL, ## directory_to_save = NULL, data_download_acknowledgement = FALSE, ## download = FALSE, remove_command = FALSE, unzip = TRUE, remove_zip = FALSE) ## NULL ## Test passed 😸 testthat::test_that( \"Invalid dates cause function to fail.\", { # parameters test_start <- \"1800-01-01\" test_end <- \"1800-01-02\" test_directory <- \"../inst/extdata/\" # test for error testthat::expect_error( download_hms_data( date_start = test_start, date_end = test_end, data_format = \"Shapefile\", directory_to_download = test_directory, directory_to_save = test_directory, data_download_acknowledgement = TRUE, download = FALSE, remove_command = FALSE, unzip = FALSE, remove_zip = FALSE ) ) } ) ## Test passed 😸"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"download-example","dir":"Articles","previous_headings":"","what":"Download Example","title":"download_data() and NASA EarthData Account","text":"function structure outlined unit tests place, can now perform data download. begin, check parameters required source-specific data download function. Define parameters. Download data. Checking directory shows desired data downloaded inflated, original zip files retained.","code":"names(formals(download_hms_data)) ## [1] \"date_start\" \"date_end\" ## [3] \"data_format\" \"directory_to_download\" ## [5] \"directory_to_save\" \"data_download_acknowledgement\" ## [7] \"download\" \"remove_command\" ## [9] \"unzip\" \"remove_zip\" date_start <- \"2023-12-28\" date_end <- \"2024-01-02\" data_format <- \"Shapefile\" data_directory <- \"./download_example/\" data_download_acknowledgement <- TRUE download <- TRUE # run data download remove_command <- TRUE # delete \"...commands.txt\" file unzip <- TRUE # inflate (unzip) downloaded zip files remove_zip <- FALSE # retain downloaded zip files download_data( dataset_name = \"hms\", date_start = date_start, date_end = date_end, directory_to_download = data_directory, directory_to_save = data_directory, data_download_acknowledgement = data_download_acknowledgement, download = download, remove_command = remove_command, unzip = unzip, remove_zip = remove_zip ) ## Downloading requested files... ## Requested files have been downloaded. ## Unzipping files... ## Files unzipped and saved in ./download_example/. ## Unzipping files... ## Files unzipped and saved in ./download_example/. ## Unzipping files... ## Files unzipped and saved in ./download_example/. ## Unzipping files... ## Files unzipped and saved in ./download_example/. ## Unzipping files... ## Files unzipped and saved in ./download_example/. ## Unzipping files... ## Files unzipped and saved in ./download_example/. list.files(data_directory) ## [1] \"hms_smoke_Shapefile_20231228.zip\" \"hms_smoke_Shapefile_20231229.zip\" ## [3] \"hms_smoke_Shapefile_20231230.zip\" \"hms_smoke_Shapefile_20231231.zip\" ## [5] \"hms_smoke_Shapefile_20240101.zip\" \"hms_smoke_Shapefile_20240102.zip\" ## [7] \"hms_smoke20231228.dbf\" \"hms_smoke20231228.prj\" ## [9] \"hms_smoke20231228.shp\" \"hms_smoke20231228.shx\" ## [11] \"hms_smoke20231229.dbf\" \"hms_smoke20231229.prj\" ## [13] \"hms_smoke20231229.shp\" \"hms_smoke20231229.shx\" ## [15] \"hms_smoke20231230.dbf\" \"hms_smoke20231230.prj\" ## [17] \"hms_smoke20231230.shp\" \"hms_smoke20231230.shx\" ## [19] \"hms_smoke20231231.dbf\" \"hms_smoke20231231.prj\" ## [21] \"hms_smoke20231231.shp\" \"hms_smoke20231231.shx\" ## [23] \"hms_smoke20240101.dbf\" \"hms_smoke20240101.prj\" ## [25] \"hms_smoke20240101.shp\" \"hms_smoke20240101.shx\" ## [27] \"hms_smoke20240102.dbf\" \"hms_smoke20240102.prj\" ## [29] \"hms_smoke20240102.shp\" \"hms_smoke20240102.shx\""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"nasa-earthdata-account","dir":"Articles","previous_headings":"","what":"NASA EarthData Account","title":"download_data() and NASA EarthData Account","text":"mentioned Motivation, data_download() provides access publicly available geospatial data. Although publicly available, NASA data sources require NASA EarthData Account. example, UN WPP-Adjusted population density data NASA Socioeconomic Data Applications Center (SEDAC) requires EarthData account. Without EarthData Account prerequisite files prepared, data download functions return error. downloaded file unzipped data downloaded properly.","code":"download_data( dataset_name = \"sedac_population\", year = \"2020\", data_format = \"GeoTIFF\", data_resolution = \"60 minute\", directory_to_download = \"./sedac_population/\", directory_to_save = \"./sedac_population\", data_download_acknowledgement = TRUE, download = TRUE, unzip = TRUE, remove_zip = FALSE, remove_command = TRUE ) ## Downloading requested files... ## Requested files have been downloaded. ## Unzipping files... ## ## Warning in unzip(file_name, exdir = directory_to_unzip): error 1 in extracting from zip file ## ## Files unzipped and saved in ./sedac_population/."},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"register-or-log-in","dir":"Articles","previous_headings":"NASA EarthData Account","what":"Register or log in","title":"download_data() and NASA EarthData Account","text":"Visit https://urs.earthdata.nasa.gov/ register log NASA EarthData account. Account registration provides access NASA’s Earth Observing System Data Information System (EOSDIS) twelve Distributed Active Archive Centers (DAAC), including: Alaska Satellite Facility (ASF) DAAC Atmospheric Science Data Center (ASDC) Crustal Dynamics Data Information System (CDDIS) Global Hydrometeorology Resource Center (GHRC) Goddard Earth Sciences Data Information Services Center (GES DISC) Land Processes DAAC (LP DAAC) Level 1 Atmosphere Archive Distribution System (LAADS) DAAC National Snow Ice Data Center (NSIDC) DAAC Oak Ridge National Laboratory (ORNL) DAAC Ocean Biology DAAC (OB.DAAC) Physical Oceanography DAAC (PO.DAAC) Socioeconomic Data Applications Center (SEDAC) See https://www.earthdata.nasa.gov/eosdis/daacs information.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"approved-applications","dir":"Articles","previous_headings":"NASA EarthData Account","what":"Approved applications","title":"download_data() and NASA EarthData Account","text":"creating account, navigate “Profile”(https://urs.earthdata.nasa.gov/profile), “Applications > Authorized Apps”. “Authorized Apps” page specifies NASA EarthData applications can use login credentials. example, ensure authorization enabled “SEDAC Website”, “SEDAC Website (Alpha)”, “SEDAC Website (Beta)”.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"prerequisite-files","dir":"Articles","previous_headings":"NASA EarthData Account","what":"Prerequisite files","title":"download_data() and NASA EarthData Account","text":"NASA EarthData Account required applications authorized use credentials, time create prerequisite files. Note steps produce prerequisite files specific, much code used adopted Generate Earthdata Prerequisite Files NASA GES DISC’s “-’s” webpage (link).","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"netrc","dir":"Articles","previous_headings":"NASA EarthData Account > Prerequisite files","what":".netrc","title":"download_data() and NASA EarthData Account","text":"following commands create .netrc file, contains NASA EarthData Account credentials. First, set working directory home directory. Setting working directory differs Mac/Linux Windows machines. Create file named .netrc file.create(). Open connection .netrc sink(). Write line machine urs... replacing YOUR_USERNAME YOUR_PASSWORD NASA EarthData username password, respectively. writing line, close connection sink() . Edit settings , owner file, can read write .netrc. , check ensure file created properly.","code":"if (.Platform$OS.type == \"unix\") { setwd(\"~/\") } else if (.Platform$OS.type == \"windows\") { setwd(\"C:/\") } file.create(\".netrc\") sink(\".netrc\") writeLines( \"machine urs.earthdata.nasa.gov login YOUR_USERNAME password YOUR_PASSWORD\" ) sink() system(\"chmod 0600 .netrc\") file.exists(\".netrc\") ## [1] TRUE readLines(\".netrc\") ## [1] \"machine urs.earthdata.nasa.gov login YOUR_USERNAME password YOUR_PASSWORD\""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"urs_cookies","dir":"Articles","previous_headings":"NASA EarthData Account > Prerequisite files","what":".urs_cookies","title":"download_data() and NASA EarthData Account","text":"following commands create .urs_cookies file. First, set working directory home directory. Create file named .netrc file.create(). , check ensure file created properly.","code":"if (.Platform$OS.type == \"unix\") { setwd(\"~/\") } else if (.Platform$OS.type == \"windows\") { setwd(\"C:/\") } file.create(\".urs_cookies\") file.exists(\".urs_cookies\") ## [1] TRUE"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"dodsrc","dir":"Articles","previous_headings":"NASA EarthData Account > Prerequisite files","what":".dodsrc","title":"download_data() and NASA EarthData Account","text":"following commands create .urs_cookies file. First, set working directory home directory. Create file named “.dodsrc” file.create() Open connection .dodsrc sink(). Write lines beginning HTTP., replacing YOUR_USERNAME YOUR_PASSWORD NASA EarthData username password, respectively. writing line, close connection sink() . , check ensure file created properly. working Windows machine, copy .dodsrc file project working directory. Replace YOUR_WORKING_DIRECTORY absolute path project working directory. important ensure commands, well username, password, home directory, typed without error, single problem files result failed download. files created correctly, UN WPP-Adjusted population density data NASA Socioeconomic Data Applications Center (SEDAC) downloaded unzipped without returning error.","code":"if (.Platform$OS.type == \"unix\") { setwd(\"~/\") } else if (.Platform$OS.type == \"windows\") { setwd(\"C:/\") } file.create(\".dodsrc\") sink(\".dodsrc\") writeLines( paste0( \"HTTP.NETRC=YOUR_HOME_DIRECTORY/.netrc\\n\", \"HTTP.COOKIE.JAR=YOUR_HOME_DIRECTORY/.urs_cookies\" ) ) sink() file.exists(\".dodsrc\") ## [1] TRUE readLines(\".dodsrc\") ## [1] \"HTTP.NETRC=YOUR_HOME_DIRECTORY/.netrc\" ## [2] \"HTTP.COOKIE.JAR=YOUR_HOME_DIRECTORY/.urs_cookies\" if (.Platform$OS.type == \"windows\") { file.copy( \"C:/.dodsrc\", \"YOUR_WORKING_DIRECTORY/.dodsrc\" ) } download_data( dataset_name = \"sedac_population\", year = \"2020\", data_format = \"GeoTIFF\", data_resolution = \"60 minute\", directory_to_download = \"./sedac_population/\", directory_to_save = \"./sedac_population\", data_download_acknowledgement = TRUE, download = TRUE, unzip = TRUE, remove_zip = FALSE, remove_command = TRUE ) ## Downloading requested files... ## Requested files have been downloaded. ## Unzipping files... ## Files unzipped and saved in ./sedac_population/. list.files(\"./sedac_population\") ## [1] \"gpw_v4_population_density_adjusted_to_2015_unwpp_country_totals_rev11_2020_1_deg_tif_readme.txt\" ## [2] \"gpw_v4_population_density_adjusted_to_2015_unwpp_country_totals_rev11_2020_1_deg_tif.zip\" ## [3] \"gpw_v4_population_density_adjusted_to_2015_unwpp_country_totals_rev11_2020_1_deg.tif\""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"references","dir":"Articles","previous_headings":"","what":"References","title":"download_data() and NASA EarthData Account","text":"EOSDIS Distributed Active Archive Centers (DAAC). National Aeronautics Space Administration (NASA). Date accessed: January 3, 2024. https://www.earthdata.nasa.gov/eosdis/daacs. Generate Earthdata Prerequisite Files. National Aeronautics Space Administration (NASA). Date accessed: January 3, 2024. https://disc.gsfc.nasa.gov/information/howto?title=%20to%20Generate%20Earthdata%20Prerequisite%20Files.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/download_functions.html","id":"code-example","dir":"Articles","previous_headings":"","what":"Code Example","title":"download_data() and NASA EarthData Account","text":"following entire R code used create download_hms_data().","code":"download_hms_data ## function (date_start = \"2023-09-01\", date_end = \"2023-09-01\", ## data_format = \"Shapefile\", directory_to_download = NULL, ## directory_to_save = NULL, data_download_acknowledgement = FALSE, ## download = FALSE, remove_command = FALSE, unzip = TRUE, remove_zip = FALSE) ## { ## download_permit(data_download_acknowledgement = data_download_acknowledgement) ## check_for_null_parameters(mget(ls())) ## download_setup_dir(directory_to_download) ## download_setup_dir(directory_to_save) ## directory_to_download <- download_sanitize_path(directory_to_download) ## directory_to_save <- download_sanitize_path(directory_to_save) ## if (unzip == FALSE && remove_zip == TRUE) { ## stop(paste0(\"Arguments unzip = FALSE and remove_zip = TRUE are not \", ## \"acceptable together. Please change one.\\n\")) ## } ## date_sequence <- generate_date_sequence(date_start, date_end, ## sub_hyphen = TRUE) ## base <- \"https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/\" ## commands_txt <- paste0(directory_to_download, \"hms_smoke_\", ## utils::head(date_sequence, n = 1), \"_\", utils::tail(date_sequence, ## n = 1), \"_curl_commands.txt\") ## download_sink(commands_txt) ## download_names <- NULL ## for (f in seq_along(date_sequence)) { ## year <- substr(date_sequence[f], 1, 4) ## month <- substr(date_sequence[f], 5, 6) ## if (data_format == \"Shapefile\") { ## suffix <- \".zip\" ## directory_to_cat <- directory_to_download ## } ## else if (data_format == \"KML\") { ## suffix <- \".kml\" ## directory_to_cat <- directory_to_save ## } ## url <- paste0(base, data_format, \"/\", year, \"/\", month, ## \"/hms_smoke\", date_sequence[f], suffix) ## if (f == 1) { ## if (!(check_url_status(url))) { ## sink() ## file.remove(commands_txt) ## stop(paste0(\"Invalid date returns HTTP code 404. \", ## \"Check `date_start` parameter.\\n\")) ## } ## } ## destfile <- paste0(directory_to_cat, \"hms_smoke_\", data_format, ## \"_\", date_sequence[f], suffix) ## download_names <- c(download_names, destfile) ## command <- paste0(\"curl -s -o \", destfile, \" --url \", ## url, \"\\n\") ## cat(command) ## } ## sink() ## system_command <- paste0(\". \", commands_txt, \"\\n\") ## download_run(download = download, system_command = system_command) ## download_remove_command(remove = remove_command, commands_txt = commands_txt) ## if (data_format == \"KML\") { ## return(cat(paste0(\"KML files cannot be unzipped.\\n\"))) ## } ## for (d in seq_along(download_names)) { ## download_unzip(file_name = download_names[d], directory_to_unzip = directory_to_save, ## unzip = unzip) ## } ## download_remove_zips(remove = remove_zip, download_name = download_names) ## } ## "},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/epa_download.html","id":"downloading-and-pre-processing-pre-generated-epa-aqs-data-from-their-website","dir":"Articles","previous_headings":"","what":"Downloading and pre-processing pre-generated EPA AQS data from their website","title":"Downloading EPA Daily Data","text":"script downloads pre-processed data EPA’s AQS data desired variable, year(s), temporal resolution. script also joins multiple years’ data single data frame, downloads file metadata monitors included dataset. first version script (August 2023) written download daily PM2.5 data period 2018-2022. Available datasets can found website https://aqs.epa.gov/aqsweb/airdata/download_files.html.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/epa_download.html","id":"setting-up-for-data-download","dir":"Articles","previous_headings":"Downloading and pre-processing pre-generated EPA AQS data from their website","what":"1. Setting up for data download","title":"Downloading EPA Daily Data","text":"Specifying temporal resolution, parameter interest, year Create list file URLs Specify download folder desired name downloaded zip files","code":"resolution <- \"daily\" parameter_code <- 88101 # Parameter Code for PM2.5 local conditions startyear <- 2018 endyear <- 2022 file_urls <- sprintf( paste(\"https://aqs.epa.gov/aqsweb/airdata/\", resolution, \"_\", parameter_code, \"_%.0f.zip\", sep = \"\" ), startyear:endyear ) file_urls ## [1] \"https://aqs.epa.gov/aqsweb/airdata/daily_88101_2018.zip\" ## [2] \"https://aqs.epa.gov/aqsweb/airdata/daily_88101_2019.zip\" ## [3] \"https://aqs.epa.gov/aqsweb/airdata/daily_88101_2020.zip\" ## [4] \"https://aqs.epa.gov/aqsweb/airdata/daily_88101_2021.zip\" ## [5] \"https://aqs.epa.gov/aqsweb/airdata/daily_88101_2022.zip\" download_dir <- \"../input/aqs/\" download_names <- sprintf( paste(download_dir, \"download_output_%.0f.zip\", sep = \"\" ), startyear:endyear ) download_names ## [1] \"../input/aqs/download_output_2018.zip\" ## [2] \"../input/aqs/download_output_2019.zip\" ## [3] \"../input/aqs/download_output_2020.zip\" ## [4] \"../input/aqs/download_output_2021.zip\" ## [5] \"../input/aqs/download_output_2022.zip\""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/epa_download.html","id":"downloading-data","dir":"Articles","previous_headings":"Downloading and pre-processing pre-generated EPA AQS data from their website","what":"2. Downloading data","title":"Downloading EPA Daily Data","text":"Download zip files website Construct string unzipped file names","code":"download.file(file_urls, download_names, method = \"libcurl\") csv_names <- sprintf( paste(download_dir, resolution, \"_\", parameter_code, \"_%.0f.csv\", sep = \"\" ), startyear:endyear )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/epa_download.html","id":"processing-data","dir":"Articles","previous_headings":"Downloading and pre-processing pre-generated EPA AQS data from their website","what":"3. Processing data","title":"Downloading EPA Daily Data","text":"Unzip read .csv files, process join one dataframe. unique site identifier “ID.Code” string structure State-County-Site-Parameter-POC","code":"for (n in seq_along(file_urls)) { # Unzips file to same folder it was downloaded to unzip(download_names[n], exdir = download_dir) # Read in dataframe print(paste(\"reading and processing file:\", csv_names[n], \"...\")) data <- read.csv(csv_names[n], stringsAsFactors = FALSE) # Make unique site identifier: State-County-Site-Parameter-POC data$ID.Code <- paste(data$State.Code, data$County.Code, data$Site.Num, data$Parameter.Code, data$POC, sep = \"-\" ) # Concatenate with other years if (n == 1) { data_all <- data } else { data_all <- rbind(data_all, data) } } ## [1] \"reading and processing file:../input/aqs/daily_88101_2018.csv...\" ## [1] \"reading and processing file:../input/aqs/daily_88101_2019.csv...\" ## [1] \"reading and processing file:../input/aqs/daily_88101_2020.csv...\" ## [1] \"reading and processing file:../input/aqs/daily_88101_2021.csv...\" ## [1] \"reading and processing file:../input/aqs/daily_88101_2022.csv...\""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/epa_download.html","id":"downloading-monitor-metadata-file-and-filter-for-relevant-sites","dir":"Articles","previous_headings":"Downloading and pre-processing pre-generated EPA AQS data from their website","what":"4. Downloading monitor metadata file and filter for relevant sites","title":"Downloading EPA Daily Data","text":"Download monitors file Unzip read Create site identifier Filter monitors file include monitors csv","code":"destfile <- paste(download_dir, \"aqs_monitors.zip\", sep = \"\") download.file(\"https://aqs.epa.gov/aqsweb/airdata/aqs_monitors.zip\", destfile) unzip(destfile, exdir = download_dir) monitors <- read.csv(\"../input/aqs/aqs_monitors.csv\", stringsAsFactors = FALSE) # Convert from string to numeric to get rid of leading zeros, # the NAs introduced are from monitors in Canada with site number=\"CC\" monitors$State.Code <- as.numeric(monitors$State.Code) monitors$ID.Code <- paste(monitors$State.Code, monitors$County.Code, monitors$Site.Num, monitors$Parameter.Code, monitors$POC, sep = \"-\" ) monitors <- read.csv(\"../input/aqs/aqs_monitors.csv\", stringsAsFactors = FALSE ) monitors_filter <- monitors[which(monitors$ID.Code %in% data_all$ID.Code), ]"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/articles/epa_download.html","id":"uploading-data-to-desired-folder","dir":"Articles","previous_headings":"Downloading and pre-processing pre-generated EPA AQS data from their website","what":"5. Uploading data to desired folder","title":"Downloading EPA Daily Data","text":"","code":"savepath <- \"../input/aqs/\" write.csv(data_all, paste(savepath, resolution, \"_\", parameter_code, \"_\", startyear, \"-\", endyear, \".csv\", sep = \"\" )) write.csv(monitors_filter, paste(savepath, \"monitors_\", parameter_code, \"_\", startyear, \"-\", endyear, \".csv\", sep = \"\" ))"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Kyle Messier. Author, maintainer. Mitchell Manware. Author, contributor. Insang Song. Author, contributor. Eva Marques. Author, contributor. Mariana Alifa Kassien. Author, contributor. Ranadeep Daw. Author, contributor. Daniel Zilber. Author, contributor.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Messier K, Manware M, Song , Marques E, Alifa Kassien M, Daw R, Zilber D (2024). amadeus: AMADEUS: Mechanism/Machine Data, Environments, User Setup. R package version 0.1.3, , https://github.com/Spatiotemporal-Exposures--Toxicology/amadeus.","code":"@Manual{, title = {amadeus: AMADEUS: A Mechanism/Machine for Data, Environments, and User Setup}, author = {Kyle Messier and Mitchell Manware and Insang Song and Eva Marques and Mariana {Alifa Kassien} and Ranadeep Daw and Daniel Zilber}, year = {2024}, note = {R package version 0.1.3, }, url = {https://github.com/Spatiotemporal-Exposures-and-Toxicology/amadeus}, }"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/index.html","id":"amadeus","dir":"","previous_headings":"","what":"AMADEUS: A Mechanism/Machine for Data, Environments, and User Setup","title":"AMADEUS: A Mechanism/Machine for Data, Environments, and User Setup","text":"Mechanism/Machine Data, Environments, User Setup amadeus R package devloped improve expideite users’ access large, publicly available geospatial data sets. functions amadeus allow users download import cleaned geospatial data directly R, useful automated run scripts, analysis pipelines, reproducible science general.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/index.html","id":"download","dir":"","previous_headings":"","what":"Download","title":"AMADEUS: A Mechanism/Machine for Data, Environments, and User Setup","text":"download_data() accesses downloads raw geospatial data variety open source data repositories. function wrapper calls source-specific download functions, account source’s unique combination URL, file naming conventions, data types. Download functions cover following sources: See download_functions vignette detailed description source-specific download functions. Example use download_data() using NOAA NCEP North American Regional Reanalysis’s (NARR) “weasd” (Daily Accumulated Snow Surface) variable.","code":"> download_data( + dataset_name = \"narr_monolevel\", + year_start = 2022, + year_end = 2022, + variable = \"weasd\", + directory_to_save = directory_to_save, + data_download_acknowledgement = TRUE, + download = TRUE + ) Downloading requested files... Requested files have been downloaded. > list.files(paste0(directory_to_save, \"weasd/\")) [1] \"weasd.2022.nc\""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/index.html","id":"process","dir":"","previous_headings":"","what":"Process","title":"AMADEUS: A Mechanism/Machine for Data, Environments, and User Setup","text":"process() imports cleans raw geospatial data (downloaded download()), returns single SpatRaster SpatVector user’s R environment. process() “cleans” data defining interpretable layer names, ensuring coordinate reference system present, managing time data (applicable). avoid errors using process(), edit raw downloaded data files. Passing user-generated edited data procces() may result errors underlying functions adapted sources’ raw data file type. Example use process() using downloaded “weasd” data.","code":"> weasd <- process_narr( + date = c(\"2022-01-01\", \"2022-01-05\"), + variable = \"weasd\", + path = path + ) Cleaning weasd data for year 2022... Returning daily weasd data from 2022-01-01 to 2022-01-05. > weasd class : SpatRaster dimensions : 277, 349, 5 (nrow, ncol, nlyr) resolution : 32462.99, 32463 (x, y) extent : -16231.49, 11313351, -16231.5, 8976020 (xmin, xmax, ymin, ymax) coord. ref. : +proj=lcc +lat_0=50 +lon_0=-107 +lat_1=50 +lat_2=50 +x_0=5632642.22547 +y_0=4612545.65137 +datum=WGS84 +units=m +no_defs source : weasd.2022.nc:weasd varname : weasd (Daily Accumulated Snow at Surface) names : weasd_20220101, weasd_20220102, weasd_20220103, weasd_20220104, weasd_20220105 unit : kg/m^2, kg/m^2, kg/m^2, kg/m^2, kg/m^2 time : 2022-01-01 to 2022-01-05 UTC"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/index.html","id":"calculate-covariates","dir":"","previous_headings":"","what":"Calculate Covariates","title":"AMADEUS: A Mechanism/Machine for Data, Environments, and User Setup","text":"calc_covariates() stems beethoven package, air pollution model’s (citation) need various types data extracted precise locations. calc_covariates(), therefore, extracts data “cleaned” SpatRaster SpatVector object user defined locations. Users can choose buffer locations. function returns data.frame data extracted locations layer row SpatRaster SpatVector object, respectively. Example calc_covariates() using processed “weasd” data.","code":"> weasd_covar <- calc_narr( + from = weasd, + locs = locs, + locs_id = \"site_id\", + radius = 0 + ) Converting data.table to data.frame... Projecting data to desired coordinate reference system... Utilizing 0 meter buffer for covariate calculations. Calculating daily weasd covariates at monolevel for date 2022-01-01... Calculating daily weasd covariates at monolevel for date 2022-01-02... Calculating daily weasd covariates at monolevel for date 2022-01-03... Calculating daily weasd covariates at monolevel for date 2022-01-04... Calculating daily weasd covariates at monolevel for date 2022-01-05... Returning weasd covariates. > weasd_covar site_id date level weasd_0 1 37183001488101 2022-01-01 monolevel 0.000000000 2 37183002188101 2022-01-01 monolevel 0.000000000 3 37063001588101 2022-01-01 monolevel 0.000000000 4 37183001488101 2022-01-02 monolevel 0.000000000 5 37183002188101 2022-01-02 monolevel 0.000000000 6 37063001588101 2022-01-02 monolevel 0.000000000 7 37183001488101 2022-01-03 monolevel 0.000000000 8 37183002188101 2022-01-03 monolevel 0.000000000 9 37063001588101 2022-01-03 monolevel 0.000000000 10 37183001488101 2022-01-04 monolevel 0.000000000 11 37183002188101 2022-01-04 monolevel 0.000000000 12 37063001588101 2022-01-04 monolevel 0.000000000 13 37183001488101 2022-01-05 monolevel 0.003906250 14 37183002188101 2022-01-05 monolevel 0.001953125 15 37063001588101 2022-01-05 monolevel 0.001953125"},{"path":[]},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/as_mysftime.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert to sftime object on the form adapted to beethoven code — as_mysftime","title":"Convert to sftime object on the form adapted to beethoven code — as_mysftime","text":"Convert sftime object form adapted beethoven code","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/as_mysftime.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert to sftime object on the form adapted to beethoven code — as_mysftime","text":"","code":"as_mysftime(x, ...)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/as_mysftime.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert to sftime object on the form adapted to beethoven code — as_mysftime","text":"x data.frame, data.table, SpatVector SpatRasterDataset ... x data.frame data.table: lonname, latname, timename crs arguments required. x sf sftime, timename argument required. x terra::SpatRaster, varname argument required.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/as_mysftime.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert to sftime object on the form adapted to beethoven code — as_mysftime","text":"sftime object constrained time column name (see check_mysftime() function)","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/as_mysftime.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Convert to sftime object on the form adapted to beethoven code — as_mysftime","text":"Eva Marques","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_covariates.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate covariates — calc_covariates","title":"Calculate covariates — calc_covariates","text":"Calculate covariates","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_covariates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate covariates — calc_covariates","text":"","code":"calc_covariates( covariate = c(\"modis\", \"koppen-geiger\", \"koeppen-geiger\", \"koppen\", \"koeppen\", \"geos\", \"dummies\", \"gmted\", \"roads\", \"ecoregions\", \"ecoregion\", \"hms\", \"noaa\", \"smoke\", \"gmted\", \"narr\", \"narr_monolevel\", \"narr_p_levels\", \"plevels\", \"monolevel\", \"p_levels\", \"geos\", \"sedac_population\", \"population\"), locs, from, locs_id = \"site_id\", ... )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_covariates.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate covariates — calc_covariates","text":"covariate character(1). Covariate type. locs sf/SpatVector. Unique locations. include unique identifier field named locs_id character. Single multiple strings. locs_id character(1). Name unique identifier. Default \"site_id\". ... Arguments passed covariate calculation function.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_covariates.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate covariates — calc_covariates","text":"Calculated covariates. Mainly data.frame object.","code":""},{"path":[]},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_covariates.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate covariates — calc_covariates","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_ecoregion.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate EPA Ecoregions level 2/3 binary variables — calc_ecoregion","title":"Calculate EPA Ecoregions level 2/3 binary variables — calc_ecoregion","text":"Calculate EPA Ecoregions level 2/3 binary variables","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_ecoregion.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate EPA Ecoregions level 2/3 binary variables — calc_ecoregion","text":"","code":"calc_ecoregion(locs, from = NULL, locs_id = \"site_id\", ...)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_ecoregion.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate EPA Ecoregions level 2/3 binary variables — calc_ecoregion","text":"locs sf/SpatVector. Unique locs. include unique identifier field named locs_id SpatVector. Ecoregion polygons locs_id character(1). Name unique identifier. ... Placeholders.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_ecoregion.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate EPA Ecoregions level 2/3 binary variables — calc_ecoregion","text":"data.frame object dummy variables attributes : attr(., \"ecoregion2_code\"): Ecoregion lv.2 code key attr(., \"ecoregion3_code\"): Ecoregion lv.3 code key","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_ecoregion.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate EPA Ecoregions level 2/3 binary variables — calc_ecoregion","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_geos.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate NASA GEOS-CF meteorological and atmospheric covariates — calc_geos","title":"Calculate NASA GEOS-CF meteorological and atmospheric covariates — calc_geos","text":"Extract GEOS-CF data point locations using SpatRaster object process_geos. Function returns data frame containing GEOS-CF variable values user-defined sites. Unique column names reflect variable name, circular buffer, vertical pressure level (applicable).","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_geos.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate NASA GEOS-CF meteorological and atmospheric covariates — calc_geos","text":"","code":"calc_geos(from, locs, locs_id = NULL, radius = 0, fun = \"mean\")"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_geos.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate NASA GEOS-CF meteorological and atmospheric covariates — calc_geos","text":"SpatRaster(1). Cleaned SpatRaster object returned process_eos containing GEOS-CF variable data. locs data.frame, characater file path, SpatVector, sf object. locs_id character(1). Column within locations CSV file containing identifier unique coordinate location. radius integer(1). Circular buffer distance around site locations. (Default = 0). fun character(1). Function used summarize multiple raster cells within sites location buffer (Default = mean).","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_geos.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate NASA GEOS-CF meteorological and atmospheric covariates — calc_geos","text":"data.frame object;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_geos.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate NASA GEOS-CF meteorological and atmospheric covariates — calc_geos","text":"Mitchell Manware","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_gmted.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate GMTED elevation covariates — calc_gmted","title":"Calculate GMTED elevation covariates — calc_gmted","text":"Extract Global Multi-resolution Terrain Elevation Data (GMTED2010) data point locations using SpatRaster object process_gmted. Function returns data frame containing GMTED variable values user-defined sites. Unique column reflect statistic, resolution, circular buffer.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_gmted.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate GMTED elevation covariates — calc_gmted","text":"","code":"calc_gmted(from, locs, locs_id = NULL, radius = 0, fun = \"mean\")"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_gmted.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate GMTED elevation covariates — calc_gmted","text":"SpatRaster(1). Cleaned SpatRaster object returned process_gmted containing Global Multi-resolution Terrain Elevation Data (GMTED2010) data. locs data.frame. character file path, SpatVector, sf object. locs_id character(1). Column within locations CSV file containing identifier unique coordinate location. radius integer(1). Circular buffer distance around site locations. (Default = 0). fun character(1). Function used summarize multiple raster cells within sites location buffer (Default = mean).","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_gmted.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate GMTED elevation covariates — calc_gmted","text":"data.frame object;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_gmted.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate GMTED elevation covariates — calc_gmted","text":"Mitchell Manware","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_hms.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate NOAA HMS Wildfire Smoke covariates — calc_hms","title":"Calculate NOAA HMS Wildfire Smoke covariates — calc_hms","text":"Extract wildfire smoke plume coverage data NOAA Hazard Mapping Fire Smoke Product point locations using SpatVector object process_hms. Function returns data frame containing wildfire smoke plume binary values (0 = smoke absent; 1 = smoke present) user-defined sites. Unique columns reflect smoke density circular buffer.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_hms.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate NOAA HMS Wildfire Smoke covariates — calc_hms","text":"","code":"calc_hms(from, locs, locs_id = NULL, radius = 0)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_hms.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate NOAA HMS Wildfire Smoke covariates — calc_hms","text":"SpatVector(1). Cleaned SpatVector object returned process_hms containing wildfire smoke plume coverage data. locs data.frame, characater file path, SpatVector, sf object. locs_id character(1). Column within locations CSV file containing identifier unique coordinate location. radius integer(1). Circular buffer distance around site locations. (Default = 0).","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_hms.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate NOAA HMS Wildfire Smoke covariates — calc_hms","text":"data.frame object;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_hms.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate NOAA HMS Wildfire Smoke covariates — calc_hms","text":"Mitchell Manware","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_koppen_geiger.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate Koeppen-Geiger climate zone binary variables — calc_koppen_geiger","title":"Calculate Koeppen-Geiger climate zone binary variables — calc_koppen_geiger","text":"Calculate Koeppen-Geiger climate zone binary variables","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_koppen_geiger.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate Koeppen-Geiger climate zone binary variables — calc_koppen_geiger","text":"","code":"calc_koppen_geiger(locs = NULL, from = NULL, locs_id = \"site_id\", ...)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_koppen_geiger.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate Koeppen-Geiger climate zone binary variables — calc_koppen_geiger","text":"locs sf/SpatVector. Unique locs. include unique identifier field named locs_id character(1). Koppen-Geiger climate zone raster file locs_id character(1). Name unique identifier. ... Placeholders.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_koppen_geiger.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate Koeppen-Geiger climate zone binary variables — calc_koppen_geiger","text":"data.frame object","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_koppen_geiger.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate Koeppen-Geiger climate zone binary variables — calc_koppen_geiger","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_modis_daily.html","id":null,"dir":"Reference","previous_headings":"","what":"A single-date MODIS worker for parallelization — calc_modis_daily","title":"A single-date MODIS worker for parallelization — calc_modis_daily","text":"modis_worker operates six MODIS/VIIRS products (MOD11A1, MOD13A2, MOD06_L2, VNP46A2, MOD09GA, MCD19A2) daily basis. Given raw hdf files downloaded NASA, standard file names include data retrieval date flag starting . Leveraging piece information, function select files scope date interest. Please note function provide function filter swaths tiles, strongly recommended check pre-filter file names users' discretion.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_modis_daily.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"A single-date MODIS worker for parallelization — calc_modis_daily","text":"","code":"calc_modis_daily( locs = NULL, from = NULL, locs_id = \"site_id\", date = NULL, name_extracted = NULL, fun_summary = \"mean\", radius = 0L, ... )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_modis_daily.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"A single-date MODIS worker for parallelization — calc_modis_daily","text":"locs SpatVector/sf/sftime object. Locations MODIS values summarized. SpatRaster. Preprocessed objects. locs_id character(1). Field name unique site identifiers stored. Default \"site_id\" date Date(1). date query. name_extracted character. Names calculated covariates. fun_summary function. Summary function multilayer rasters. Passed foo. See exactextractr::exact_extract details. radius numeric. Radius generate circular buffers. ... Placeholders.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_modis_daily.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"A single-date MODIS worker for parallelization — calc_modis_daily","text":"data.frame object.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_modis_daily.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"A single-date MODIS worker for parallelization — calc_modis_daily","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_modis_par.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate MODIS product covariates in multiple CPU threads — calc_modis_par","title":"Calculate MODIS product covariates in multiple CPU threads — calc_modis_par","text":"calc_modis_par essentially runs calc_modis_daily function thread (subprocess). Based daily resolution, day's workload distributed thread. product argument, files processed customized function unique structure /characteristics products considered. nthreads argument carefully selected consideration machine's CPU memory capacities products memory pressure. locs sf object exportable parallel workers.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_modis_par.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate MODIS product covariates in multiple CPU threads — calc_modis_par","text":"","code":"calc_modis_par( locs = NULL, from = NULL, locs_id = \"site_id\", preprocess = process_modis_merge, name_covariates = NULL, radius = c(0L, 1000L, 10000L, 50000L), subdataset = NULL, fun_summary = \"mean\", nthreads = floor(length(parallelly::availableWorkers())/2), package_list_add = NULL, export_list_add = NULL, ... )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_modis_par.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate MODIS product covariates in multiple CPU threads — calc_modis_par","text":"locs sf/SpatVector object. Unique locs covariates calculated. character. List paths MODIS/VIIRS files. locs_id character(1). Site identifier. Default \"site_id\" preprocess function. Function handle HDF files. name_covariates character. Name header covariates. e.g., \"MOD_NDVIF_0_\". calculated covariate names form 'name_covariateszero-padded buffer radius meters', e.g., 'MOD_NDVIF_0_50000' 50 km radius circular buffer used calculate mean NDVI value. radius numeric. Radii calculate covariates. Default c(0, 1000, 10000, 50000). subdataset Index search pattern subdataset. fun_summary character function. Function summarize extracted raster values. nthreads integer(1). Number threads used calculate covariates. package_list_add character. vector package names load thread. Note sf, terra, exactextractr, doParallel, parallelly dplyr default packages loaded. export_list_add character. vector object names export thread. minimized spare memory. ... Arguments passed preprocess.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_modis_par.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate MODIS product covariates in multiple CPU threads — calc_modis_par","text":"Overall, function dependent routines assume file system can handle concurrent access (network) disk multiple processes. File system characteristics, package versions, hardware settings specification can affect processing efficiency. locs expected convertible sf object. sf, SpatVector, class objects converted sf can used. Common arguments preprocess functions date path automatically detected passed function. Please note locs path preprocess functions assumed standard naming convention raw files NASA.","code":""},{"path":[]},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_narr.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate NOAA NCEP North American Regional Reanalysis meteorological\nand atmospheric covariates — calc_narr","title":"Calculate NOAA NCEP North American Regional Reanalysis meteorological\nand atmospheric covariates — calc_narr","text":"Extract NOAA NCEP North American Regional Reanalysis (NARR) data point locations using SpatRaster object process_narr. Function returns data frame containing NARR variable values user-defined sites. Unique column names reflect variable name, circular buffer, vertical pressure level (applicable).","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_narr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate NOAA NCEP North American Regional Reanalysis meteorological\nand atmospheric covariates — calc_narr","text":"","code":"calc_narr(from, locs, locs_id = NULL, radius = 0, fun = \"mean\")"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_narr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate NOAA NCEP North American Regional Reanalysis meteorological\nand atmospheric covariates — calc_narr","text":"SpatRaster(1). Cleaned SpatRaster object returned process_narr containing NOAA NCEP North American Regional Reanalysis variable data. locs data.frame, characater file path, SpatVector, sf object. locs_id character(1). Column within locations CSV file containing identifier unique coordinate location. radius integer(1). Circular buffer distance around site locations. (Default = 0). fun character(1). Function used summarize multiple raster cells within sites location buffer (Default = mean).","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_narr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate NOAA NCEP North American Regional Reanalysis meteorological\nand atmospheric covariates — calc_narr","text":"data.frame object;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_narr.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate NOAA NCEP North American Regional Reanalysis meteorological\nand atmospheric covariates — calc_narr","text":"Mitchell Manware","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_nei.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate National Emission Inventory (NEI) covariates — calc_nei","title":"Calculate National Emission Inventory (NEI) covariates — calc_nei","text":"Calculate National Emission Inventory (NEI) covariates","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_nei.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate National Emission Inventory (NEI) covariates — calc_nei","text":"","code":"calc_nei(locs = NULL, from = NULL, locs_id = \"site_id\", ...)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_nei.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate National Emission Inventory (NEI) covariates — calc_nei","text":"locs sf/SpatVector. Locations NEI values joined. character(1). directory NEI CSV files locs_id character(1). Unique site identifier column name. Unused kept compatibility. ... Placeholders.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_nei.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate National Emission Inventory (NEI) covariates — calc_nei","text":"data.frame object.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_nei.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate National Emission Inventory (NEI) covariates — calc_nei","text":"Insang Song, Ranadeep Daw","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_nlcd_ratio.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute land cover classes ratio in circle buffers around points — calc_nlcd_ratio","title":"Compute land cover classes ratio in circle buffers around points — calc_nlcd_ratio","text":"Compute land cover classes ratio circle buffers around points","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_nlcd_ratio.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute land cover classes ratio in circle buffers around points — calc_nlcd_ratio","text":"","code":"calc_nlcd_ratio(locs, from, locs_id = \"site_id\", radius = 1000, ...)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_nlcd_ratio.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute land cover classes ratio in circle buffers around points — calc_nlcd_ratio","text":"locs terra::SpatVector points geometry SpatRaster NLCD locs_id character(1). Unique identifier locations radius numeric (non-negative) giving radius buffer around points ... Placeholders.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedac_groads.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate SEDAC groads density covariates — calc_sedac_groads","title":"Calculate SEDAC groads density covariates — calc_sedac_groads","text":"Prepared groads data clipped buffer polygons radius. total length roads calculated. density roads calculated dividing total length area buffer. terra::linearUnits() used convert unit length meters.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedac_groads.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate SEDAC groads density covariates — calc_sedac_groads","text":"","code":"calc_sedac_groads( from = NULL, locs = NULL, locs_id = NULL, radius = 1000, fun = sum )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedac_groads.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate SEDAC groads density covariates — calc_sedac_groads","text":"SpatVector(1). Output process_sedac_groads. locs data.frame, characater file path, SpatVector, sf object. locs_id character(1). Column within locations CSV file containing identifier unique coordinate location. radius integer(1). Circular buffer distance around site locations. (Default = 1000). fun function(1). Function used summarize length roads within sites location buffer (Default sum).","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedac_groads.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate SEDAC groads density covariates — calc_sedac_groads","text":"data.frame object three columns.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedac_groads.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate SEDAC groads density covariates — calc_sedac_groads","text":"Unit km / sq km.","code":""},{"path":[]},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedac_groads.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate SEDAC groads density covariates — calc_sedac_groads","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedac_population.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate UN WPP-Ajusted population density covariates — calc_sedac_population","title":"Calculate UN WPP-Ajusted population density covariates — calc_sedac_population","text":"Extract population density data point locations using SpatRaster object process_sedac_population. Function returns data frame containing population values user-defined sites. Unique column names reflect variable name circular buffer.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedac_population.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate UN WPP-Ajusted population density covariates — calc_sedac_population","text":"","code":"calc_sedac_population(from, locs, locs_id = NULL, radius = 0, fun = \"mean\")"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedac_population.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate UN WPP-Ajusted population density covariates — calc_sedac_population","text":"SpatRaster(1). Cleaned SpatRaster object returned process_sedac_population containing GEOS-CF variable data. locs data.frame, characater file path, SpatVector, sf object. locs_id character(1). Column within locations CSV file containing identifier unique coordinate location. radius integer(1). Circular buffer distance around site locations. (Default = 0). fun character(1). Function used summarize multiple raster cells within sites location buffer (Default = mean).","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedac_population.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate UN WPP-Ajusted population density covariates — calc_sedac_population","text":"data.frame object;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedac_population.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate UN WPP-Ajusted population density covariates — calc_sedac_population","text":"Mitchell Manware","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedc.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate Sum of Exponentially Decaying Contributions (SEDC) covariates — calc_sedc","title":"Calculate Sum of Exponentially Decaying Contributions (SEDC) covariates — calc_sedc","text":"Calculate Sum Exponentially Decaying Contributions (SEDC) covariates","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedc.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate Sum of Exponentially Decaying Contributions (SEDC) covariates — calc_sedc","text":"","code":"calc_sedc( locs = NULL, from = NULL, locs_id = NULL, sedc_bandwidth = NULL, target_fields = NULL )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedc.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate Sum of Exponentially Decaying Contributions (SEDC) covariates — calc_sedc","text":"locs SpatVector object. Locations sum SEDCs calculated. SpatVector object. Locations SEDC calculated. locs_id character(1). Name unique id field point_to. sedc_bandwidth numeric(1). Distance source concentration reduced exp(-3) (approximately -95 %) target_fields character(varying). Field names characters.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedc.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate Sum of Exponentially Decaying Contributions (SEDC) covariates — calc_sedc","text":"data.frame (tibble) object input field names suffix \"_sedc\" sums EDC stored. Additional attributes attached EDC information. `attr(result, \"sedc_bandwidth\")``: bandwidth concentration reduces approximately five percent `attr(result, \"sedc_threshold\")``: threshold distance emission source points excluded beyond ","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedc.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate Sum of Exponentially Decaying Contributions (SEDC) covariates — calc_sedc","text":"function originally chopin Distance calculation done terra functions internally. Thus, function internally converts sf objects point_* arguments terra. threshold carefully chosen users.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedc.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculate Sum of Exponentially Decaying Contributions (SEDC) covariates — calc_sedc","text":"Messier KP, Akita Y, & Serre ML. (2012). Integrating Address Geocoding, Land Use Regression, Spatiotemporal Geostatistical Estimation Groundwater Tetrachloroethylene. Environmental Science & Technology 46(5), 2772-2780. Wiesner C. (n.d.). Euclidean Sum Exponentially Decaying Contributions Tutorial","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedc.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate Sum of Exponentially Decaying Contributions (SEDC) covariates — calc_sedc","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_sedc.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate Sum of Exponentially Decaying Contributions (SEDC) covariates — calc_sedc","text":"","code":"library(terra) #> terra 1.7.71 library(sf) #> Linking to GEOS 3.10.2, GDAL 3.4.1, PROJ 8.2.1; sf_use_s2() is TRUE set.seed(101) ncpath <- system.file(\"gpkg/nc.gpkg\", package = \"sf\") nc <- terra::vect(ncpath) nc <- terra::project(nc, \"EPSG:5070\") pnt_locs <- terra::centroids(nc, inside = TRUE) pnt_locs <- pnt_locs[, \"NAME\"] pnt_from <- terra::spatSample(nc, 100L) pnt_from$pid <- seq(1, 100) pnt_from <- pnt_from[, \"pid\"] pnt_from$val1 <- rgamma(100L, 1, 0.05) pnt_from$val2 <- rgamma(100L, 2, 1) vals <- c(\"val1\", \"val2\") calc_sedc(pnt_locs, pnt_from, \"NAME\", 1e5, vals) #> Joining with `by = join_by(from_id)` #> Joining with `by = join_by(to_id)` #> Joining with `by = join_by(from_id, to_id)` #> # A tibble: 100 × 3 #> NAME val1 val2 #> #> 1 Alamance 66.3 6.71 #> 2 Alexander 98.0 11.7 #> 3 Alleghany 135. 8.57 #> 4 Anson 50.0 5.23 #> 5 Ashe 143. 8.42 #> 6 Avery 76.1 8.76 #> 7 Beaufort 58.8 6.29 #> 8 Bertie 70.1 7.85 #> 9 Bladen 79.5 6.82 #> 10 Brunswick 54.3 5.34 #> # ℹ 90 more rows"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_temporal_dummies.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate temporal dummy variables — calc_temporal_dummies","title":"Calculate temporal dummy variables — calc_temporal_dummies","text":"Calculate temporal dummy variables","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_temporal_dummies.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate temporal dummy variables — calc_temporal_dummies","text":"","code":"calc_temporal_dummies( locs, from = NULL, locs_id = \"site_id\", year = seq(2018L, 2022L), ... )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_temporal_dummies.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate temporal dummy variables — calc_temporal_dummies","text":"locs data.frame temporal field named \"time\" used. locs_id character(1). Unique site identifier column name. Default \"site_id\". year integer. Year domain dummify. Default seq(2018L, 2022L) ... Placeholders.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_temporal_dummies.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate temporal dummy variables — calc_temporal_dummies","text":"data.frame year, month, weekday indicators.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_temporal_dummies.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate temporal dummy variables — calc_temporal_dummies","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_tri.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate TRI covariates — calc_tri","title":"Calculate TRI covariates — calc_tri","text":"Calculate TRI covariates","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_tri.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate TRI covariates — calc_tri","text":"","code":"calc_tri( locs, from = NULL, locs_id = \"site_id\", radius = c(1000L, 10000L, 50000L), ... )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_tri.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate TRI covariates — calc_tri","text":"locs sf/SpatVector. Locations TRI variables calculated. SpatVector. Point vector object TRI year. See process_tri locs_id character(1). Unique site identifier column name. Default \"site_id\". radius Circular buffer radius. Default c(1000, 10000, 50000) (meters) ... Placeholders.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_tri.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate TRI covariates — calc_tri","text":"data.frame object.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_tri.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate TRI covariates — calc_tri","text":"U.S. context.","code":""},{"path":[]},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/calc_tri.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate TRI covariates — calc_tri","text":"Insang Song, Mariana Kassien","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_for_null_parameters.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for null arguments — check_for_null_parameters","title":"Check for null arguments — check_for_null_parameters","text":"Check null arguments","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_for_null_parameters.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for null arguments — check_for_null_parameters","text":"","code":"check_for_null_parameters(parameters)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_for_null_parameters.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for null arguments — check_for_null_parameters","text":"parameters parameters passed function (called mget(ls()).)","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_mysf.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if the sf object is formated on a specific way — check_mysf","title":"Check if the sf object is formated on a specific way — check_mysf","text":"Check sf object formated specific way","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_mysf.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if the sf object is formated on a specific way — check_mysf","text":"","code":"check_mysf(x)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_mysf.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if the sf object is formated on a specific way — check_mysf","text":"x sf object","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_mysf.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Check if the sf object is formated on a specific way — check_mysf","text":"Eva Marques","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_mysftime.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if the sftime object is formated on a specific way — check_mysftime","title":"Check if the sftime object is formated on a specific way — check_mysftime","text":"Check sftime object formated specific way","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_mysftime.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if the sftime object is formated on a specific way — check_mysftime","text":"","code":"check_mysftime(x)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_mysftime.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if the sftime object is formated on a specific way — check_mysftime","text":"x sftime object","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_mysftime.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Check if the sftime object is formated on a specific way — check_mysftime","text":"Eva Marques","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_url_status.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if sample of download URLs have HTTP Status 200 — check_url_status","title":"Check if sample of download URLs have HTTP Status 200 — check_url_status","text":"Check sample download URLs HTTP Status 200","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_url_status.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if sample of download URLs have HTTP Status 200 — check_url_status","text":"","code":"check_url_status(url, method = c(\"HEAD\", \"GET\"))"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_url_status.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if sample of download URLs have HTTP Status 200 — check_url_status","text":"url Download URL checked. method httr method obtain URL (\"HEAD\" \"GET\")","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_url_status.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if sample of download URLs have HTTP Status 200 — check_url_status","text":"logical object","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_url_status.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Check if sample of download URLs have HTTP Status 200 — check_url_status","text":"Insang Song; Mitchell Manware","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_urls.html","id":null,"dir":"Reference","previous_headings":"","what":"Sample download URLs and apply check_url_status function — check_urls","title":"Sample download URLs and apply check_url_status function — check_urls","text":"Sample download URLs apply check_url_status function","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_urls.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Sample download URLs and apply check_url_status function — check_urls","text":"","code":"check_urls(urls = urls, size = NULL, method = c(\"HEAD\", \"GET\", \"SKIP\"))"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_urls.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Sample download URLs and apply check_url_status function — check_urls","text":"urls character vector URLs size number observations sampled urls method httr method obtain URL (\"HEAD\" \"GET\"). set \"SKIP\", HTTP status checked returned.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/check_urls.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Sample download URLs and apply check_url_status function — check_urls","text":"logical vector URL status = 200","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_aqs_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download daily data from AQS datamart — download_aqs_data","title":"Download daily data from AQS datamart — download_aqs_data","text":"Download daily data AQS datamart","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_aqs_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download daily data from AQS datamart — download_aqs_data","text":"","code":"download_aqs_data( parameter_code = 88101, year_start = 2018, year_end = 2022, resolution_temporal = \"daily\", directory_to_download = NULL, directory_to_save = NULL, url_aqs_download = \"https://aqs.epa.gov/aqsweb/airdata/\", data_download_acknowledgement = FALSE, unzip = TRUE, remove_zip = FALSE, download = FALSE, remove_command = FALSE )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_aqs_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download daily data from AQS datamart — download_aqs_data","text":"parameter_code integer(1). length 5. EPA pollutant parameter code. details, please refer AQS parameter codes year_start integer(1). length 4. Start year downloading data. year_end integer(1). length 4. End year downloading data. resolution_temporal character(1). Name column containing POC values. Currently, value \"daily\" works. directory_to_download character(1). Directory download zip files AQS data mart. directory_to_save character(1). Directory decompress zip files. url_aqs_download character(1). URL AQS pre-generated datasets. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. unzip logical(1). Unzip zip files. Default TRUE. remove_zip logical(1). Remove zip file directory_to_download. Default FALSE. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands. Default FALSE.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_aqs_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download daily data from AQS datamart — download_aqs_data","text":"NULL; Separate comma-separated value (CSV) files monitors daily representative values stored directory_to_save.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_aqs_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download daily data from AQS datamart — download_aqs_data","text":"Mariana Kassien, Insang Song, Mitchell Manware","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download raw data from sources — download_data","title":"Download raw data from sources — download_data","text":"Download raw data sources","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download raw data from sources — download_data","text":"","code":"download_data( dataset_name = c(\"aqs\", \"ecoregion\", \"geos\", \"gmted\", \"koppen\", \"koppengeiger\", \"merra2\", \"merra\", \"narr_monolevel\", \"modis\", \"narr_p_levels\", \"nlcd\", \"noaa\", \"sedac_groads\", \"sedac_population\", \"groads\", \"population\", \"plevels\", \"p_levels\", \"monolevel\", \"hms\", \"smoke\", \"tri\", \"nei\"), directory_to_save = NULL, data_download_acknowledgement = FALSE, ... )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download raw data from sources — download_data","text":"dataset_name character(1). Dataset download. directory_to_save character(1). Directory save / unzip (zip files downloaded) data. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. ... Arguments passed download function.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_data.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Download raw data from sources — download_data","text":"download function names download_*_data formats","code":""},{"path":[]},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download raw data from sources — download_data","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_ecoregion_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download Ecoregion Shapefiles from EPA — download_ecoregion_data","title":"Download Ecoregion Shapefiles from EPA — download_ecoregion_data","text":"download_ecoregion_data() function accesses downloads Ecoregions level 3 data, pieces information higher levels included.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_ecoregion_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download Ecoregion Shapefiles from EPA — download_ecoregion_data","text":"","code":"download_ecoregion_data( directory_to_download = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, unzip = TRUE, remove_zip = FALSE, download = FALSE, remove_command = TRUE, epa_certificate_path = system.file(\"extdata/cacert_gaftp_epa.pem\", package = \"amadeus\"), certificate_url = \"http://cacerts.digicert.com/DigiCertGlobalG2TLSRSASHA2562020CA1-1.crt\" )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_ecoregion_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download Ecoregion Shapefiles from EPA — download_ecoregion_data","text":"directory_to_download character(1). Directory download zip file Ecoregion level 3 shapefiles directory_to_save character(1). Directory decompress zip files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. unzip logical(1). Unzip zip files. Default TRUE. remove_zip logical(1). Remove zip file directory_to_download. Default FALSE. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands. epa_certificate_path character(1). Path certificate file EPA DataCommons. Default 'extdata/cacert_gaftp_epa.pem' package installation path. certificate_url character(1). URL certificate file. See notes details.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_ecoregion_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download Ecoregion Shapefiles from EPA — download_ecoregion_data","text":"NULL;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_ecoregion_data.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Download Ecoregion Shapefiles from EPA — download_ecoregion_data","text":"EPA Data Commons certificate errors, follow steps : Click Lock icon address bar https://gaftp.epa.gov Click Show Certificate Access Details Find URL *.crt extension Currently bundle pre-downloaded crt PEM (accepted wget command) file ./inst/extdata. instruction certificate updates future.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_ecoregion_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download Ecoregion Shapefiles from EPA — download_ecoregion_data","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_epa_certificate.html","id":null,"dir":"Reference","previous_headings":"","what":"Check EPA Certificate — download_epa_certificate","title":"Check EPA Certificate — download_epa_certificate","text":"Check EPA Certificate","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_epa_certificate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check EPA Certificate — download_epa_certificate","text":"","code":"download_epa_certificate( epa_certificate_path = \"cacert_gaftp_epa.pem\", certificate_url = \"http://cacerts.digicert.com/DigiCertGlobalG2TLSRSASHA2562020CA1-1.crt\" )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_epa_certificate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check EPA Certificate — download_epa_certificate","text":"epa_certificate_path character(1). Full path converted certificate EPA. end .pem certificate_url character(1). URL original certificate.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_epa_certificate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check EPA Certificate — download_epa_certificate","text":"file designated epa_certificate_path","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_epa_certificate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Check EPA Certificate — download_epa_certificate","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_geos_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download atmospheric composition data from the NASA Global Earth Observing System (GEOS) model. — download_geos_data","title":"Download atmospheric composition data from the NASA Global Earth Observing System (GEOS) model. — download_geos_data","text":"download_geos_data() function accesses downloads various atmospheric composition collections NASA Global Earth Observing System (GEOS) model.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_geos_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download atmospheric composition data from the NASA Global Earth Observing System (GEOS) model. — download_geos_data","text":"","code":"download_geos_data( date_start = \"2023-09-01\", date_end = \"2023-09-01\", collection = c(\"aqc_tavg_1hr_g1440x721_v1\", \"chm_tavg_1hr_g1440x721_v1\", \"met_tavg_1hr_g1440x721_x1\", \"xgc_tavg_1hr_g1440x721_x1\", \"chm_inst_1hr_g1440x721_p23\", \"met_inst_1hr_g1440x721_p23\"), directory_to_save = NULL, data_download_acknowledgement = FALSE, download = FALSE, remove_command = FALSE )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_geos_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download atmospheric composition data from the NASA Global Earth Observing System (GEOS) model. — download_geos_data","text":"date_start character(1). length 10. Start date downloading data. Format YYYY-MM-DD (ex. September 1, 2023 = \"2023-09-01\"). date_end character(1). length 10. End date downloading data. Format YYYY-MM-DD (ex. September 1, 2023 = \"2023-09-01\"). collection character(1). GEOS-CF data collection file name. directory_to_save character(1). Directory save data. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_geos_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download atmospheric composition data from the NASA Global Earth Observing System (GEOS) model. — download_geos_data","text":"NULL;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_geos_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download atmospheric composition data from the NASA Global Earth Observing System (GEOS) model. — download_geos_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_gmted_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download global elevation data from the Global Multi-resolution Terrain Elevation Data (GMTED2010). — download_gmted_data","title":"Download global elevation data from the Global Multi-resolution Terrain Elevation Data (GMTED2010). — download_gmted_data","text":"download_gmted_data() function acesses downloads Global Multi-resolution Terrain Elevation Data (GMTED2010) U.S. Geological Survey National Geospatial-Intelligence Agency.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_gmted_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download global elevation data from the Global Multi-resolution Terrain Elevation Data (GMTED2010). — download_gmted_data","text":"","code":"download_gmted_data( statistic = c(\"Breakline Emphasis\", \"Systematic Subsample\", \"Median Statistic\", \"Minimum Statistic\", \"Mean Statistic\", \"Maximum Statistic\", \"Standard Deviation Statistic\"), resolution = c(\"7.5 arc-seconds\", \"15 arc-seconds\", \"30 arc-seconds\"), directory_to_download = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, unzip = TRUE, remove_zip = FALSE, download = FALSE, remove_command = FALSE )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_gmted_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download global elevation data from the Global Multi-resolution Terrain Elevation Data (GMTED2010). — download_gmted_data","text":"statistic character(1). Available statistics include \"Breakline Emphasis\", \"Systematic Subsample\", \"Median Statistic\", \"Minimum Statistic\", \"Mean Statistic\", \"Maximum Statistic\", \"Standard Deviation Statistic\". resolution character(1). Available resolutions include \"7.5 arc-seconds\", \"15 arc-seconds\", \"30 arc-seconds\". directory_to_download character(1). Directory download zip files Global Multi-resolution Terrain Elevation Data (GMTED2010). directory_to_save character(1). Directory decompress zip files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. unzip logical(1). Unzip zip files. Default TRUE. remove_zip logical(1). Remove zip file directory_to_download. Default FALSE. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands. Default FALSE.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_gmted_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download global elevation data from the Global Multi-resolution Terrain Elevation Data (GMTED2010). — download_gmted_data","text":"NULL;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_gmted_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download global elevation data from the Global Multi-resolution Terrain Elevation Data (GMTED2010). — download_gmted_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_hms_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download daily wildfire smoke plume data from NOAA Hazard Mapping System Fire and Smoke Product — download_hms_data","title":"Download daily wildfire smoke plume data from NOAA Hazard Mapping System Fire and Smoke Product — download_hms_data","text":"download_hms_data() function accesses downloads wildfire smoke plume coverage data National Oceanic Atmospheric Administration's (NOAA) Hazard Mapping System Fire Smoke Product.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_hms_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download daily wildfire smoke plume data from NOAA Hazard Mapping System Fire and Smoke Product — download_hms_data","text":"","code":"download_hms_data( date_start = \"2023-09-01\", date_end = \"2023-09-01\", data_format = \"Shapefile\", directory_to_download = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, download = FALSE, remove_command = FALSE, unzip = TRUE, remove_zip = FALSE )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_hms_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download daily wildfire smoke plume data from NOAA Hazard Mapping System Fire and Smoke Product — download_hms_data","text":"date_start character(1). length 10. Start date downloading data. Format YYYY-MM-DD (ex. September 1, 2023 \"2023-09-01\"). date_end character(1). length 10. End date downloading data. Format YYYY-MM-DD (ex. September 10, 2023 \"2023-09-10\"). data_format character(1). \"Shapefile\" \"KML\". directory_to_download character(1). Directory download zip files NOAA Hazard Mapping System Fire Smoke Product. (Ignored data_format = \"KML\".) directory_to_save character(1). Directory save unzipped shapefiles KML files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands. unzip logical(1). Unzip zip files. Default TRUE. (Ignored data_format = \"KML\".) remove_zip logical(1). Remove zip files directory_to_download. Default FALSE. (Ignored data_format = \"KML\".)","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_hms_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download daily wildfire smoke plume data from NOAA Hazard Mapping System Fire and Smoke Product — download_hms_data","text":"NULL;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_hms_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download daily wildfire smoke plume data from NOAA Hazard Mapping System Fire and Smoke Product — download_hms_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_koppen_geiger_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download climate classification data from the present and future Köppen-Geiger climate classification maps. — download_koppen_geiger_data","title":"Download climate classification data from the present and future Köppen-Geiger climate classification maps. — download_koppen_geiger_data","text":"download_koppen_geiger_data() function accesses downloads climate classification data Present future Köppen-Geiger climate classification maps 1-km resolution (link article; link data).","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_koppen_geiger_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download climate classification data from the present and future Köppen-Geiger climate classification maps. — download_koppen_geiger_data","text":"","code":"download_koppen_geiger_data( time_period = c(\"Present\", \"Future\"), data_resolution = c(\"0.0083\", \"0.083\", \"0.5\"), directory_to_download = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, download = FALSE, unzip = TRUE, remove_zip = FALSE, remove_command = FALSE )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_koppen_geiger_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download climate classification data from the present and future Köppen-Geiger climate classification maps. — download_koppen_geiger_data","text":"time_period character(1). Available times \"Present\" (1980-2016) \"Future\" (2071-2100). (\"Future\" classifications based scenario RCP8.5). data_resolution character(1). Available resolutions \"0.0083\" degrees (approx. 1 km), \"0.083\" degrees (approx. 10 km), \"0.5\" degrees (approx. 50 km). directory_to_download character(1). Directory download zip files Present future Köppen-Geiger climate classification maps 1-km resolution. directory_to_save character(1). Directory decompress zip files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. unzip logical(1). Unzip zip files. Default TRUE. remove_zip logical(1). Remove zip files directory_to_download. Default FALSE. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_koppen_geiger_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download climate classification data from the present and future Köppen-Geiger climate classification maps. — download_koppen_geiger_data","text":"NULL;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_koppen_geiger_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download climate classification data from the present and future Köppen-Geiger climate classification maps. — download_koppen_geiger_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_merra2_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download meteorological and atmospheric data from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) model. — download_merra2_data","title":"Download meteorological and atmospheric data from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) model. — download_merra2_data","text":"download_merra2_data() function accesses downloads various meteorological atmospheric collections Modern-Era Retrospective analysis Research Applications, Version 2 (MERRA-2).","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_merra2_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download meteorological and atmospheric data from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) model. — download_merra2_data","text":"","code":"download_merra2_data( date_start = \"2023-09-01\", date_end = \"2023-09-01\", collection = c(\"inst1_2d_asm_Nx\", \"inst1_2d_int_Nx\", \"inst1_2d_lfo_Nx\", \"inst3_3d_asm_Np\", \"inst3_3d_aer_Nv\", \"inst3_3d_asm_Nv\", \"inst3_3d_chm_Nv\", \"inst3_3d_gas_Nv\", \"inst3_2d_gas_Nx\", \"inst6_3d_ana_Np\", \"inst6_3d_ana_Nv\", \"statD_2d_slv_Nx\", \"tavg1_2d_adg_Nx\", \"tavg1_2d_aer_Nx\", \"tavg1_2d_chm_Nx\", \"tavg1_2d_csp_Nx\", \"tavg1_2d_flx_Nx\", \"tavg1_2d_int_Nx\", \"tavg1_2d_lfo_Nx\", \"tavg1_2d_lnd_Nx\", \"tavg1_2d_ocn_Nx\", \"tavg1_2d_rad_Nx\", \"tavg1_2d_slv_Nx\", \"tavg3_3d_mst_Ne\", \"tavg3_3d_trb_Ne\", \"tavg3_3d_nav_Ne\", \"tavg3_3d_cld_Np\", \"tavg3_3d_mst_Np\", \"tavg3_3d_rad_Np\", \"tavg3_3d_tdt_Np\", \"tavg3_3d_trb_Np\", \"tavg3_3d_udt_Np\", \"tavg3_3d_odt_Np\", \"tavg3_3d_qdt_Np\", \"tavg3_3d_asm_Nv\", \"tavg3_3d_cld_Nv\", \"tavg3_3d_mst_Nv\", \"tavg3_3d_rad_Nv\", \"tavg3_2d_glc_Nx\"), directory_to_save = NULL, data_download_acknowledgement = FALSE, download = FALSE, remove_command = FALSE )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_merra2_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download meteorological and atmospheric data from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) model. — download_merra2_data","text":"date_start character(1). length 10. Start date downloading data. Format YYYY-MM-DD (ex. September 1, 2023 \"2023-09-01\"). date_end character(1). length 10. End date downloading data. Format YYYY-MM-DD (ex. September 1, 2023 \"2023-09-01\"). collection character(1). MERRA-2 data collection file name. directory_to_save character(1). Directory save data. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_merra2_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download meteorological and atmospheric data from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) model. — download_merra2_data","text":"NULL;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_merra2_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download meteorological and atmospheric data from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) model. — download_merra2_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_modis_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download MODIS product files — download_modis_data","title":"Download MODIS product files — download_modis_data","text":"Need maintenance directory path change NASA EOSDIS. function first retrieves hdf download links certain day, selects relevant tiles retrieved links. Download done queried horizontal-vertical tile number combinations. exception MOD06_L2 product, produced every five minutes every day.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_modis_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download MODIS product files — download_modis_data","text":"","code":"download_modis_data( date_start = \"2023-09-01\", date_end = \"2023-09-01\", product = c(\"MOD09GA\", \"MOD11A1\", \"MOD06_L2\", \"MCD19A2\", \"MOD13A2\", \"VNP46A2\"), version = \"61\", horizontal_tiles = c(7, 13), vertical_tiles = c(3, 6), nasa_earth_data_token = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, mod06_links = NULL, download = TRUE, remove_command = FALSE )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_modis_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download MODIS product files — download_modis_data","text":"date_start character(1). length 10. Start date downloading data. Format YYYY-MM-DD (ex. September 1, 2023 \"2023-09-01\"). date_end character(1). length 10. End date downloading data. Format YYYY-MM-DD (ex. September 1, 2023 \"2023-09-01\"). product character(1). One c(\"MOD09GA\", \"MOD11A1\", \"MOD06_L2\", \"MCD19A2\", \"MOD13A2\", \"VNP46A2\") version character(1). Default \"61\", meaning v061. horizontal_tiles integer(2). Horizontal tile numbers c({start}, {end}). Default c(7, 13). vertical_tiles integer(2). Vertical tile numbers c({start}, {end}). Default c(3, 6). nasa_earth_data_token character(1). Token downloading data NASA. set trying running function. directory_to_save character(1). Directory save data. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. mod06_links character(1). CSV file path MOD06_L2 download links NASA LPDAAC. Default NULL. download logical(1). Download data save wget commands. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_modis_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download MODIS product files — download_modis_data","text":"NULL;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_modis_data.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Download MODIS product files — download_modis_data","text":"date_start date_end year. Directory structure looks like input/modis/raw/{version}/{product}/{year}/{day_of_year} Please note date_start date_end ignored product == 'MOD06_L2'.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_modis_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download MODIS product files — download_modis_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_narr_monolevel_data.html","id":null,"dir":"Reference","previous_headings":"","what":"download_narr_monolevel_data: download monolevel meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_monolevel_data","title":"download_narr_monolevel_data: download monolevel meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_monolevel_data","text":"download_narr_monolevel_data function accesses downloads monolevel meteorological data NOAA NCEP North American Regional Reanalysis (NARR).","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_narr_monolevel_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"download_narr_monolevel_data: download monolevel meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_monolevel_data","text":"","code":"download_narr_monolevel_data( year_start = 2022, year_end = 2022, variables = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, download = FALSE, remove_command = FALSE )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_narr_monolevel_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"download_narr_monolevel_data: download monolevel meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_monolevel_data","text":"year_start integer(1). length 4. Start year range downloading data. year_end integer(1). length 4. End year range downloading data. variables character. Variable(s) name acronym. directory_to_save character(1). Directory(s) save downloaded data files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_narr_monolevel_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"download_narr_monolevel_data: download monolevel meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_monolevel_data","text":"NULL;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_narr_monolevel_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"download_narr_monolevel_data: download monolevel meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_monolevel_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_narr_p_levels_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download pressure level meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_p_levels_data","title":"Download pressure level meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_p_levels_data","text":"download_narr_p_levels_data function accesses downloads pressure level meteorological data NOAA NCEP North American Regional Reanalysis (NARR).","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_narr_p_levels_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download pressure level meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_p_levels_data","text":"","code":"download_narr_p_levels_data( year_start = 2022, year_end = 2022, variables = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, download = FALSE, remove_command = FALSE )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_narr_p_levels_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download pressure level meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_p_levels_data","text":"year_start integer(1). length 4. Start year range downloading data. year_end integer(1). length 4. End year range downloading data. variables character(1). Variable(s) name acronym. directory_to_save character(1). Directory(s) save downloaded data files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_narr_p_levels_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download pressure level meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_p_levels_data","text":"NULL;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_narr_p_levels_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download pressure level meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_p_levels_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_nei_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download data from EPA National Emission Inventory aggregated on-road emission data — download_nei_data","title":"Download data from EPA National Emission Inventory aggregated on-road emission data — download_nei_data","text":"Download data EPA National Emission Inventory aggregated -road emission data","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_nei_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download data from EPA National Emission Inventory aggregated on-road emission data — download_nei_data","text":"","code":"download_nei_data( directory_to_save = NULL, data_download_acknowledgement = FALSE, download = FALSE, remove_command = FALSE, year_target = c(2017L, 2020L), unzip = FALSE, epa_certificate_path = system.file(\"extdata/cacert_gaftp_epa.pem\", package = \"amadeus\"), certificate_url = \"http://cacerts.digicert.com/DigiCertGlobalG2TLSRSASHA2562020CA1-1.crt\" )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_nei_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download data from EPA National Emission Inventory aggregated on-road emission data — download_nei_data","text":"directory_to_save character(1). Directory download files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands. year_target Available years NEI data. Default c(2017L, 2020L). unzip logical(1). Unzip downloaded zip files. Default FALSE. epa_certificate_path character(1). Path certificate file EPA DataCommons. Default 'extdata/cacert_gaftp_epa.pem' package installation path. certificate_url character(1). URL certificate file. See notes details.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_nei_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download data from EPA National Emission Inventory aggregated on-road emission data — download_nei_data","text":"NULL; Two comma-separated value (CSV) raw files 2017 2020","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_nei_data.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Download data from EPA National Emission Inventory aggregated on-road emission data — download_nei_data","text":"EPA Data Commons certificate errors, follow steps : Click Lock icon address bar https://gaftp.epa.gov Click Show Certificate Access Details Find URL *.crt extension Currently bundle pre-downloaded crt PEM (accepted wget command) file ./inst/extdata. instruction certificate updates future.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_nei_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download data from EPA National Emission Inventory aggregated on-road emission data — download_nei_data","text":"Ranadeep Daw, Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_nlcd_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download land cover data from the National Land Cover Database Science Research Products. — download_nlcd_data","title":"Download land cover data from the National Land Cover Database Science Research Products. — download_nlcd_data","text":"download_nlcd_data() function accesses downloads land cover data NLCD Science Research Products data base.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_nlcd_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download land cover data from the National Land Cover Database Science Research Products. — download_nlcd_data","text":"","code":"download_nlcd_data( year = 2021, collection = \"Coterminous United States\", directory_to_download = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, unzip = TRUE, remove_zip = FALSE, download = FALSE, remove_command = FALSE )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_nlcd_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download land cover data from the National Land Cover Database Science Research Products. — download_nlcd_data","text":"year integer(1). Available years Coterminous United States include 2001, 2004, 2006, 2008, 2011, 2013, 2016, 2019, 2021. Available years Alaska include 2001, 2011, 2016. collection character(1). \"Coterminous United States\" \"Alaska\". directory_to_download character(1). Directory download zip files National Land Cover Database Science Research Products. directory_to_save character(1). Directory decompress zip files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. unzip logical(1). Unzip zip files. Default TRUE. remove_zip logical(1). Remove zip files directory_to_download. Default FALSE. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_nlcd_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download land cover data from the National Land Cover Database Science Research Products. — download_nlcd_data","text":"NULL;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_nlcd_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download land cover data from the National Land Cover Database Science Research Products. — download_nlcd_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_permit.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for data download acknowledgement — download_permit","title":"Check for data download acknowledgement — download_permit","text":"Check data download acknowledgement","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_permit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for data download acknowledgement — download_permit","text":"","code":"download_permit(data_download_acknowledgement)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_permit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for data download acknowledgement — download_permit","text":"data_download_acknowledgement logical(1). Whether start downloading","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_remove_command.html","id":null,"dir":"Reference","previous_headings":"","what":"Remove or keep wget command file — download_remove_command","title":"Remove or keep wget command file — download_remove_command","text":"Remove keep wget command file","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_remove_command.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Remove or keep wget command file — download_remove_command","text":"","code":"download_remove_command(commands_txt = NULL, remove = FALSE)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_remove_command.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Remove or keep wget command file — download_remove_command","text":"commands_txt character(1). Path download commands remove logical(1). Remove (TRUE) keep (FALSE) commands","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_remove_zips.html","id":null,"dir":"Reference","previous_headings":"","what":"Remove downloaded zip files — download_remove_zips","title":"Remove downloaded zip files — download_remove_zips","text":"Remove downloaded zip files","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_remove_zips.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Remove downloaded zip files — download_remove_zips","text":"","code":"download_remove_zips(remove = FALSE, download_name)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_remove_zips.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Remove downloaded zip files — download_remove_zips","text":"remove logical(1). Confirm removal. Default FALSE. download_name character. Full zip file path","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_run.html","id":null,"dir":"Reference","previous_headings":"","what":"download_run: execute or skip system_command\nin data download function. — download_run","title":"download_run: execute or skip system_command\nin data download function. — download_run","text":"Execute skip commands listed ...wget/curl_commands.txt file produced one data download functions.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_run.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"download_run: execute or skip system_command\nin data download function. — download_run","text":"","code":"download_run(download = FALSE, system_command = NULL)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_run.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"download_run: execute or skip system_command\nin data download function. — download_run","text":"download logical(1). Execute (TRUE) skip (FALSE) download. system_command character(1). Linux command execute downloads. Inherited data download function.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_sanitize_path.html","id":null,"dir":"Reference","previous_headings":"","what":"Sanitize path to end with a forward slash — download_sanitize_path","title":"Sanitize path to end with a forward slash — download_sanitize_path","text":"Sanitize path end forward slash","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_sanitize_path.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Sanitize path to end with a forward slash — download_sanitize_path","text":"","code":"download_sanitize_path(directory)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_sanitize_path.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Sanitize path to end with a forward slash — download_sanitize_path","text":"directory character(1). Path","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_sanitize_path.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Sanitize path to end with a forward slash — download_sanitize_path","text":"character ending forward slash.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_sedac_groads_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download Global Roads Open Access Data Set (gROADS), v1 (1980-2010) data from NASA Socioeconomic Data and Applications Center (SEDAC). — download_sedac_groads_data","title":"Download Global Roads Open Access Data Set (gROADS), v1 (1980-2010) data from NASA Socioeconomic Data and Applications Center (SEDAC). — download_sedac_groads_data","text":"download_sedac_groads_data() function accesses downloads roads data National Aeronautics Space Administration's (NASA) Global Roads Open Access Data Set.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_sedac_groads_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download Global Roads Open Access Data Set (gROADS), v1 (1980-2010) data from NASA Socioeconomic Data and Applications Center (SEDAC). — download_sedac_groads_data","text":"","code":"download_sedac_groads_data( data_format = c(\"Shapefile\", \"Geodatabase\"), data_region = c(\"Americas\", \"Global\", \"Africa\", \"Asia\", \"Europe\", \"Oceania East\", \"Oceania West\"), directory_to_download = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, unzip = TRUE, remove_zip = FALSE, download = FALSE, remove_command = FALSE )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_sedac_groads_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download Global Roads Open Access Data Set (gROADS), v1 (1980-2010) data from NASA Socioeconomic Data and Applications Center (SEDAC). — download_sedac_groads_data","text":"data_format character(1). Data can downloaded \"Shapefile\" \"Geodatabase\". (\"Geodatabase\" available \"Global\" region). data_region character(1). Data can downloaded \"Global\", \"Africa\", \"Asia\", \"Europe\", \"Americas\", \"Oceania East\", \"Oceania West\". directory_to_download character(1). Directory download zip files NASA Global Roads Open Access Data Set. directory_to_save character(1). Directory decompress zip files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. unzip logical(1). Unzip zip files. Default TRUE. remove_zip logical(1). Remove zip files directory_to_download. Default FALSE. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_sedac_groads_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download Global Roads Open Access Data Set (gROADS), v1 (1980-2010) data from NASA Socioeconomic Data and Applications Center (SEDAC). — download_sedac_groads_data","text":"NULL;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_sedac_groads_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download Global Roads Open Access Data Set (gROADS), v1 (1980-2010) data from NASA Socioeconomic Data and Applications Center (SEDAC). — download_sedac_groads_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_sedac_population_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download UN WPP-Adjusted population density data from NASA Socioeconomic Data and Applications Center (SEDAC) — download_sedac_population_data","title":"Download UN WPP-Adjusted population density data from NASA Socioeconomic Data and Applications Center (SEDAC) — download_sedac_population_data","text":"download_sedac_population_data() function accesses downloads population density data National Aeronatuics Space Administration's (NASA) UN WPP-Adjusted Population Density, v4.11.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_sedac_population_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download UN WPP-Adjusted population density data from NASA Socioeconomic Data and Applications Center (SEDAC) — download_sedac_population_data","text":"","code":"download_sedac_population_data( year = \"2020\", data_format = c(\"GeoTIFF\", \"ASCII\", \"netCDF\"), data_resolution = \"60 minute\", directory_to_download = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, download = FALSE, unzip = TRUE, remove_zip = FALSE, remove_command = FALSE )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_sedac_population_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download UN WPP-Adjusted population density data from NASA Socioeconomic Data and Applications Center (SEDAC) — download_sedac_population_data","text":"year character(1). Available years 2000, 2005, 2010, 2015, 2020, \"\" years. data_format character(1). Individual year data can downloaded \"ASCII\" \"GeoTIFF\". \"\" years downloaded \"netCDF\". data_resolution character(1). Available resolutions 30 second (approx. 1 km), 2.5 minute (approx. 5 km), 15 minute (approx. 30 km), 30 minute (approx. 55 km), 60 minute (approx. 110 km). directory_to_download character(1). Directory download zip files NASA UN WPP-Adjusted Population Density, v4.11. directory_to_save character(1). Directory decompress zip files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. unzip logical(1). Unzip zip files. Default TRUE. remove_zip logical(1). Remove zip files directory_to_download. Default FALSE. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_sedac_population_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download UN WPP-Adjusted population density data from NASA Socioeconomic Data and Applications Center (SEDAC) — download_sedac_population_data","text":"NULL;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_sedac_population_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download UN WPP-Adjusted population density data from NASA Socioeconomic Data and Applications Center (SEDAC) — download_sedac_population_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_setup_dir.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if input directory exists — download_setup_dir","title":"Check if input directory exists — download_setup_dir","text":"directory exist, directory created.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_setup_dir.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if input directory exists — download_setup_dir","text":"","code":"download_setup_dir(directory)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_setup_dir.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if input directory exists — download_setup_dir","text":"directory character(1) directory path","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_sink.html","id":null,"dir":"Reference","previous_headings":"","what":"Start sink download commands into a text file — download_sink","title":"Start sink download commands into a text file — download_sink","text":"Start sink download commands text file","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_sink.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Start sink download commands into a text file — download_sink","text":"","code":"download_sink(command_txt)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_sink.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Start sink download commands into a text file — download_sink","text":"command_txt character(1). file path export commands.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_tri_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download data from EPA toxic release inventory — download_tri_data","title":"Download data from EPA toxic release inventory — download_tri_data","text":"Download data EPA toxic release inventory","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_tri_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download data from EPA toxic release inventory — download_tri_data","text":"","code":"download_tri_data( year_start = 2018L, year_end = 2022L, directory_to_save = NULL, data_download_acknowledgement = FALSE, download = FALSE, remove_command = FALSE )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_tri_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download data from EPA toxic release inventory — download_tri_data","text":"year_start integer(1). length 4. Start year downloading data. year_end integer(1). length 4. End year downloading data. directory_to_save character(1). Directory download files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_tri_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download data from EPA toxic release inventory — download_tri_data","text":"NULL; Yearly comma-separated value (CSV) raw files year","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_tri_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download data from EPA toxic release inventory — download_tri_data","text":"Mariana Kassien, Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_unzip.html","id":null,"dir":"Reference","previous_headings":"","what":"Unzip downloaded data — download_unzip","title":"Unzip downloaded data — download_unzip","text":"Unzip downloaded data","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_unzip.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Unzip downloaded data — download_unzip","text":"","code":"download_unzip(file_name, directory_to_unzip, unzip = TRUE)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/download_unzip.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Unzip downloaded data — download_unzip","text":"file_name character(1). Full zip file path directory_to_unzip character(1). Directory unzip data unzip logical(1). Unzip (TRUE) .","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/dt_as_mysftime.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a sftime from a datatable — dt_as_mysftime","title":"Create a sftime from a datatable — dt_as_mysftime","text":"Create sftime datatable","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/dt_as_mysftime.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a sftime from a datatable — dt_as_mysftime","text":"","code":"dt_as_mysftime(x, lonname, latname, timename, crs)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/dt_as_mysftime.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a sftime from a datatable — dt_as_mysftime","text":"x data.table lonname character longitude column name latname character latitude column name timename character time column name crs coordinate reference system","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/dt_as_mysftime.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a sftime from a datatable — dt_as_mysftime","text":"sftime object","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/dt_as_mysftime.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Create a sftime from a datatable — dt_as_mysftime","text":"Eva Marques","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/extract_urls.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract URLs from download commands — extract_urls","title":"Extract URLs from download commands — extract_urls","text":"Extract URLs download commands","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/extract_urls.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract URLs from download commands — extract_urls","text":"","code":"extract_urls(commands = commands, position = NULL)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/extract_urls.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract URLs from download commands — extract_urls","text":"commands character vector containing download commands position URL position vector","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/extract_urls.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract URLs from download commands — extract_urls","text":"character vector containing download URLs","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/generate_date_sequence.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate sequence of dates based on date_start and date_end. — generate_date_sequence","title":"Generate sequence of dates based on date_start and date_end. — generate_date_sequence","text":"Generate sequence dates based date_start date_end.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/generate_date_sequence.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate sequence of dates based on date_start and date_end. — generate_date_sequence","text":"","code":"generate_date_sequence(date_start, date_end, sub_hyphen = TRUE)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/generate_date_sequence.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate sequence of dates based on date_start and date_end. — generate_date_sequence","text":"date_start character(1). Beginning date sequence. date_end character(1). End date sequence. sub_hyphen logical(1). Substitute hyphen dates. TRUE, returns date sequence \"YYYYMMDD\". FALSE, returns date sequence \"YYYY-MM-DD\".","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/generate_date_sequence.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate sequence of dates based on date_start and date_end. — generate_date_sequence","text":"vector","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/generate_time_sequence.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate time sequence based on GEOS-CF data collection. — generate_time_sequence","title":"Generate time sequence based on GEOS-CF data collection. — generate_time_sequence","text":"Generate time sequence based GEOS-CF data collection.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/generate_time_sequence.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate time sequence based on GEOS-CF data collection. — generate_time_sequence","text":"","code":"generate_time_sequence(collection)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/generate_time_sequence.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate time sequence based on GEOS-CF data collection. — generate_time_sequence","text":"collection character(1). GEOS-CF data collection","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/generate_time_sequence.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate time sequence based on GEOS-CF data collection. — generate_time_sequence","text":"vector","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/is_date_proper.html","id":null,"dir":"Reference","previous_headings":"","what":"Check input strings conform to the required format — is_date_proper","title":"Check input strings conform to the required format — is_date_proper","text":"Check input strings conform required format","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/is_date_proper.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check input strings conform to the required format — is_date_proper","text":"","code":"is_date_proper(instr = NULL, format = \"%Y-%m-%d\")"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/is_date_proper.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check input strings conform to the required format — is_date_proper","text":"instr character(1). String check. format character(1). Matching format checked. Default \"%Y-%m-%d\", can detect \"%Y/%m/%d. See strftime details formatting string.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/is_date_proper.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check input strings conform to the required format — is_date_proper","text":"returning value. stops function instr conform format.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/is_date_proper.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Check input strings conform to the required format — is_date_proper","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_aqs.html","id":null,"dir":"Reference","previous_headings":"","what":"Filter unique AQS sites with or without temporal information — process_aqs","title":"Filter unique AQS sites with or without temporal information — process_aqs","text":"Filter unique AQS sites without temporal information","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_aqs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filter unique AQS sites with or without temporal information — process_aqs","text":"","code":"process_aqs( path = NULL, date = c(\"2018-01-01\", \"2022-12-31\"), return_format = \"terra\" )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_aqs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filter unique AQS sites with or without temporal information — process_aqs","text":"path character(1). Directory path daily measurement data. date character(2). Start end date. \"YYYY-MM-DD\" format sorted. NULL, unique locations returned. return_format character(1). \"terra\" \"sf\".","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_aqs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filter unique AQS sites with or without temporal information — process_aqs","text":"SpatVector sf object depending return_format.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_aqs.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Filter unique AQS sites with or without temporal information — process_aqs","text":"date = NULL return massive data.table object. Please choose proper date values.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_bluemarble.html","id":null,"dir":"Reference","previous_headings":"","what":"Assign VIIRS Blue Marble products corner coordinates to retrieve a merged raster — process_bluemarble","title":"Assign VIIRS Blue Marble products corner coordinates to retrieve a merged raster — process_bluemarble","text":"function return SpatRaster object georeferenced h5 files Blue Marble product. Referencing corner coordinates necessary original h5 data include information.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_bluemarble.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assign VIIRS Blue Marble products corner coordinates to retrieve a merged raster — process_bluemarble","text":"","code":"process_bluemarble( path = NULL, date = NULL, tile_df = process_bluemarble_corners(), subdataset = 3L, crs = \"EPSG:4326\", ... )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_bluemarble.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assign VIIRS Blue Marble products corner coordinates to retrieve a merged raster — process_bluemarble","text":"path character. Full paths h5 files. date character(1). Date query. tile_df data.frame. Contains four corner coordinates fields named c(\"xmin\", \"xmax\", \"ymin\", \"ymax\"). See process_bluemarble_corners generate valid object argument. subdataset integer(1). Subdataset number process. Default 3L. crs character(1). terra::crs compatible CRS. Default \"EPSG:4326\" ... internal use.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_bluemarble.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assign VIIRS Blue Marble products corner coordinates to retrieve a merged raster — process_bluemarble","text":"SpatRaster.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_bluemarble.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Assign VIIRS Blue Marble products corner coordinates to retrieve a merged raster — process_bluemarble","text":"Wang, Z. (2022). Blue Marble User Guide (Version 1.3). NASA.","code":""},{"path":[]},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_bluemarble.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Assign VIIRS Blue Marble products corner coordinates to retrieve a merged raster — process_bluemarble","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_bluemarble_corners.html","id":null,"dir":"Reference","previous_headings":"","what":"Tile corner generator for Blue Marble products — process_bluemarble_corners","title":"Tile corner generator for Blue Marble products — process_bluemarble_corners","text":"Blue Marble products HDF5 format read without georeference typical R geospatial packages. function generates data.frame corner coordinates assignment.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_bluemarble_corners.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tile corner generator for Blue Marble products — process_bluemarble_corners","text":"","code":"process_bluemarble_corners(hrange = c(5, 11), vrange = c(3, 6))"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_bluemarble_corners.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tile corner generator for Blue Marble products — process_bluemarble_corners","text":"hrange integer(2). 0-35. vrange integer(2). 0-17.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_bluemarble_corners.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tile corner generator for Blue Marble products — process_bluemarble_corners","text":"data.frame xmin, xmax, ymin, ymax fields.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_bluemarble_corners.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Tile corner generator for Blue Marble products — process_bluemarble_corners","text":"Wang, Z. (2022). Blue Marble User Guide (Version 1.3). NASA.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_bluemarble_corners.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tile corner generator for Blue Marble products — process_bluemarble_corners","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_conformity.html","id":null,"dir":"Reference","previous_headings":"","what":"Check input assumptions — process_conformity","title":"Check input assumptions — process_conformity","text":"Check \"lon\", \"lat\", \"time\" (check_time = TRUE) convert inputs SpatVector object.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_conformity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check input assumptions — process_conformity","text":"","code":"process_conformity(locs = NULL, check_time = FALSE, locs_epsg = \"EPSG:4326\")"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_conformity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check input assumptions — process_conformity","text":"locs Data. sf, SpatVector, data.frame check_time logical(1). Whether \"time\" exists column names. locs_epsg character(1). \"{authority}:{code}\" Well-Known Text format coordinate reference system definition.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_conformity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check input assumptions — process_conformity","text":"SpatVector object.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_conformity.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Check input assumptions — process_conformity","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_covariates.html","id":null,"dir":"Reference","previous_headings":"","what":"Process covariates — process_covariates","title":"Process covariates — process_covariates","text":"Process covariates","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_covariates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Process covariates — process_covariates","text":"","code":"process_covariates( covariate = c(\"modis_swath\", \"modis_merge\", \"koppen-geiger\", \"bluemarble\", \"koeppen-geiger\", \"koppen\", \"koeppen\", \"geos\", \"dummies\", \"gmted\", \"hms\", \"smoke\", \"sedac_population\", \"population\", \"sedac_groads\", \"groads\", \"roads\", \"nlcd\", \"tri\", \"narr\", \"nei\", \"ecoregions\", \"ecoregion\"), path = NULL, ... )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_covariates.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Process covariates — process_covariates","text":"covariate character(1). Covariate type. path character(1). Directory file path raw data depending covariate value. ... Arguments passed raw data processing function.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_covariates.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Process covariates — process_covariates","text":"SpatVector SpatRaster depending covariate type.","code":""},{"path":[]},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_covariates.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Process covariates — process_covariates","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_ecoregion.html","id":null,"dir":"Reference","previous_headings":"","what":"Process EPA Ecoregion shapefiles — process_ecoregion","title":"Process EPA Ecoregion shapefiles — process_ecoregion","text":"Process EPA Ecoregion shapefiles","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_ecoregion.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Process EPA Ecoregion shapefiles — process_ecoregion","text":"","code":"process_ecoregion(path = NULL)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_ecoregion.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Process EPA Ecoregion shapefiles — process_ecoregion","text":"path character(1). Path Ecoregion Shapefiles","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_ecoregion.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Process EPA Ecoregion shapefiles — process_ecoregion","text":"SpatVector object.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_ecoregion.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Process EPA Ecoregion shapefiles — process_ecoregion","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_flatten_sds.html","id":null,"dir":"Reference","previous_headings":"","what":"Aggregate layers in a sub-dataset in sinusoidal MODIS products — process_flatten_sds","title":"Aggregate layers in a sub-dataset in sinusoidal MODIS products — process_flatten_sds","text":"MODIS products consist multi-layer subdatasets. function aggregates multiple layers single layer SpatRaster. fun_agg applied overlapping cells.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_flatten_sds.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Aggregate layers in a sub-dataset in sinusoidal MODIS products — process_flatten_sds","text":"","code":"process_flatten_sds(path = NULL, subdataset = NULL, fun_agg = \"mean\")"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_flatten_sds.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Aggregate layers in a sub-dataset in sinusoidal MODIS products — process_flatten_sds","text":"path character(1). Full path MODIS HDF4/HDF5 file. Direct sub-dataset access supported, example, HDF4_EOS:EOS_GRID:{filename}:{base_grid_information}:{sub-dataset} subdataset character(1). Exact regular expression filter sub-dataset. See process_modis_sds details. fun_agg character(1). Function name aggregate layers. acceptable terra::tapp.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_flatten_sds.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Aggregate layers in a sub-dataset in sinusoidal MODIS products — process_flatten_sds","text":"SpatRaster.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_flatten_sds.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Aggregate layers in a sub-dataset in sinusoidal MODIS products — process_flatten_sds","text":"HDF values read original without scaling. Users consult MODIS product documentation apply proper scaling factor post-hoc adjustment. users preliminary information MODIS sub-datasets, consider running terra::describe(__filename__, sds = TRUE) navigate full list sub-datasets input file consult documentation MODIS product.","code":""},{"path":[]},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_flatten_sds.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Aggregate layers in a sub-dataset in sinusoidal MODIS products — process_flatten_sds","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_geos.html","id":null,"dir":"Reference","previous_headings":"","what":"Import and clean GEOS-CF data downloaded with\ndownload_geos_data or download_data(dataset_name = ","title":"Import and clean GEOS-CF data downloaded with\ndownload_geos_data or download_data(dataset_name = ","text":"Import clean GEOS-CF data downloaded download_geos_data download_data(dataset_name = \"geos\"). Function returns SpatRast object containing user-defined variables interest. Layer names indicate variable, pressure level, date (YYYYMMDD), , applicable, hour (HHMMSS).","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_geos.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import and clean GEOS-CF data downloaded with\ndownload_geos_data or download_data(dataset_name = ","text":"","code":"process_geos( date = c(\"2018-01-01\", \"2018-01-01\"), variable = NULL, path = NULL )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_geos.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import and clean GEOS-CF data downloaded with\ndownload_geos_data or download_data(dataset_name = ","text":"date character(2). length 10. Format \"YYYY-MM-DD\". variable character(1). GEOS-CF variable name(s). path character(1). Directory downloaded GEOS-CF netCDF files.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_geos.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import and clean GEOS-CF data downloaded with\ndownload_geos_data or download_data(dataset_name = ","text":"SpatRaster object;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_geos.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Import and clean GEOS-CF data downloaded with\ndownload_geos_data or download_data(dataset_name = ","text":"Mitchell Manware","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_geos_collection.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify GEOS-CF collection based on user-defined file paths — process_geos_collection","title":"Identify GEOS-CF collection based on user-defined file paths — process_geos_collection","text":"Identify GEOS-CF collection based user-defined file paths","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_geos_collection.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify GEOS-CF collection based on user-defined file paths — process_geos_collection","text":"","code":"process_geos_collection( path, collection = FALSE, date = FALSE, datetime = FALSE )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_geos_collection.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify GEOS-CF collection based on user-defined file paths — process_geos_collection","text":"path character(1). File path GEOS-CF data file. collection logical(1). Identifies returns GEOS-CF collection name(s) based provided file path(s). date logical(1). Identifies returns date sequence (YYYYMMDD) based provided file path(s). datetime logical(1). Identifies returns date time sequence (YYYYMoMoDDHHMiMi) based provided file path(s).","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_geos_collection.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify GEOS-CF collection based on user-defined file paths — process_geos_collection","text":"character","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_gmted.html","id":null,"dir":"Reference","previous_headings":"","what":"Import and clean Global Multi-resolution Terrain Elevation Data (GMTED2010)\ndownloaded with download_gmted or download_data(dataset_name = ","title":"Import and clean Global Multi-resolution Terrain Elevation Data (GMTED2010)\ndownloaded with download_gmted or download_data(dataset_name = ","text":"Import clean Global Multi-resolution Terrain Elevation Data (GMTED2010) downloaded download_gmted download_data(dataset_name = \"gmted\"). Function returns SpatRast object containing user-defined variable interest specified resolution. Layer name indicates variable resolution.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_gmted.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import and clean Global Multi-resolution Terrain Elevation Data (GMTED2010)\ndownloaded with download_gmted or download_data(dataset_name = ","text":"","code":"process_gmted(variable = NULL, path = NULL)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_gmted.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import and clean Global Multi-resolution Terrain Elevation Data (GMTED2010)\ndownloaded with download_gmted or download_data(dataset_name = ","text":"variable vector(1). Vector containing GMTED statistic first resolution second. (Example: variable = c(\"Breakline Emphasis\", \"7.5 arc-seconds\")). path character(1). Directory downloaded GEOS-CF \"*_grd\" folder containing .adf files.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_gmted.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import and clean Global Multi-resolution Terrain Elevation Data (GMTED2010)\ndownloaded with download_gmted or download_data(dataset_name = ","text":"SpatRaster object","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_gmted.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Import and clean Global Multi-resolution Terrain Elevation Data (GMTED2010)\ndownloaded with download_gmted or download_data(dataset_name = ","text":"Mitchell Manware","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_gmted_codes.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate statistic and resolution codes based on GMTED statistic and\nresolution. — process_gmted_codes","title":"Generate statistic and resolution codes based on GMTED statistic and\nresolution. — process_gmted_codes","text":"Generate statistic resolution codes based GMTED statistic resolution.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_gmted_codes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate statistic and resolution codes based on GMTED statistic and\nresolution. — process_gmted_codes","text":"","code":"process_gmted_codes( string, statistic = FALSE, resolution = FALSE, invert = FALSE )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_gmted_codes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate statistic and resolution codes based on GMTED statistic and\nresolution. — process_gmted_codes","text":"string character(1). File path GEOS-CF data file. statistic logical(1). Matches statistic statistic code. resolution logical(1). Matches resolution resolution code. invert logical(1). Default = FALSE. invert = TRUE assumes string provides statistic resolution code, returns full length statistic resolution.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_gmted_codes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate statistic and resolution codes based on GMTED statistic and\nresolution. — process_gmted_codes","text":"character","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_hms.html","id":null,"dir":"Reference","previous_headings":"","what":"Import and clean wildfire smoke plume coverage data from NOAA Hazard\nMapping System Fire and Smoke Product. — process_hms","title":"Import and clean wildfire smoke plume coverage data from NOAA Hazard\nMapping System Fire and Smoke Product. — process_hms","text":"Import clean wildfire smoke plume coverage data NOAA Hazard Mapping System Fire Smoke Product.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_hms.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import and clean wildfire smoke plume coverage data from NOAA Hazard\nMapping System Fire and Smoke Product. — process_hms","text":"","code":"process_hms( date = c(\"2018-01-01\", \"2018-01-01\"), variable = c(\"Light\", \"Medium\", \"Heavy\"), path = NULL )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_hms.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import and clean wildfire smoke plume coverage data from NOAA Hazard\nMapping System Fire and Smoke Product. — process_hms","text":"date character(2). length 10 . Start/end date downloaded data. Format YYYY-MM-DD (ex. September 1, 2023 = \"2023-09-01\"). variable character(1). \"Light\", \"Medium\", \"Heavy\". path character(1). Directory downloaded NOAA HMS data files.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_hms.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import and clean wildfire smoke plume coverage data from NOAA Hazard\nMapping System Fire and Smoke Product. — process_hms","text":"SpatVector object;","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_hms.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Import and clean wildfire smoke plume coverage data from NOAA Hazard\nMapping System Fire and Smoke Product. — process_hms","text":"Mitchell Manware.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_koppen_geiger.html","id":null,"dir":"Reference","previous_headings":"","what":"Process Koeppen-Geiger climate data — process_koppen_geiger","title":"Process Koeppen-Geiger climate data — process_koppen_geiger","text":"Process Koeppen-Geiger climate data","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_koppen_geiger.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Process Koeppen-Geiger climate data — process_koppen_geiger","text":"","code":"process_koppen_geiger(path = NULL, year = NULL)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_koppen_geiger.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Process Koeppen-Geiger climate data — process_koppen_geiger","text":"path character(1). Path Koppen-Geiger climate zone raster file year data year. applicable function.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_koppen_geiger.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Process Koeppen-Geiger climate data — process_koppen_geiger","text":"SpatRaster object","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_koppen_geiger.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Process Koeppen-Geiger climate data — process_koppen_geiger","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_locs_radius.html","id":null,"dir":"Reference","previous_headings":"","what":"Create circular buffer around site points. — process_locs_radius","title":"Create circular buffer around site points. — process_locs_radius","text":"Creates circular buffer around points radius > 0. Returns points radius 0.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_locs_radius.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create circular buffer around site points. — process_locs_radius","text":"","code":"process_locs_radius(locs, radius)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_locs_radius.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create circular buffer around site points. — process_locs_radius","text":"locs SpatVector(1). SpatVector object point geometry radius integer(1). Circular buffer size (meters).","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_locs_radius.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create circular buffer around site points. — process_locs_radius","text":"SpatVector.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_locs_vector.html","id":null,"dir":"Reference","previous_headings":"","what":"Import and prepare site point locations for covariate calculations. — process_locs_vector","title":"Import and prepare site point locations for covariate calculations. — process_locs_vector","text":"Import prepare site point locations covariate calculations.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_locs_vector.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import and prepare site point locations for covariate calculations. — process_locs_vector","text":"","code":"process_locs_vector(locs, crs, radius)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_locs_vector.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import and prepare site point locations for covariate calculations. — process_locs_vector","text":"locs data.frame(1). Data frame containing columns unique identifier, latitute, longitude. Latitude longitude columns must named \"lat\" \"lon\", respectively. crs Coordinate reference system (CRS) description utilizing terra::crs(). radius integer(1). Circular buffer size (meters).","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_locs_vector.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import and prepare site point locations for covariate calculations. — process_locs_vector","text":"SpatVector","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_merge.html","id":null,"dir":"Reference","previous_headings":"","what":"Get mosaicked or merged raster from multiple MODIS hdf files — process_modis_merge","title":"Get mosaicked or merged raster from multiple MODIS hdf files — process_modis_merge","text":"Get mosaicked merged raster multiple MODIS hdf files","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_merge.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get mosaicked or merged raster from multiple MODIS hdf files — process_modis_merge","text":"","code":"process_modis_merge( path = NULL, date = NULL, subdataset = NULL, fun_agg = \"mean\", ... )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_merge.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get mosaicked or merged raster from multiple MODIS hdf files — process_modis_merge","text":"path character. Full list hdf file paths. preferably recursive search result list.files. date character(1). date query. \"YYYY-MM-DD\" format. subdataset character(1). subdataset names extract. conform regular expression. See regex details. Default NULL, result errors. Users specify subdatasets imported. fun_agg Function name custom function aggregate overlapping cell values. See fun description tapp details. ... internal use.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_merge.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get mosaicked or merged raster from multiple MODIS hdf files — process_modis_merge","text":"SpatRaster object.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_merge.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Get mosaicked or merged raster from multiple MODIS hdf files — process_modis_merge","text":"Curvilinear products (.e., swaths) accepted. MODIS products downloaded functions amadeus, MODISTools, luna accepted.","code":""},{"path":[]},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_merge.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Get mosaicked or merged raster from multiple MODIS hdf files — process_modis_merge","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_sds.html","id":null,"dir":"Reference","previous_headings":"","what":"Selected MODIS sinusoidal grid product subdataset name selector — process_modis_sds","title":"Selected MODIS sinusoidal grid product subdataset name selector — process_modis_sds","text":"Four presets supported. custom_sel supersedes presets product values.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_sds.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Selected MODIS sinusoidal grid product subdataset name selector — process_modis_sds","text":"","code":"process_modis_sds( product = c(\"MOD11A1\", \"MOD13A2\", \"MOD09GA\", \"MCD19A2\"), custom_sel = NULL )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_sds.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Selected MODIS sinusoidal grid product subdataset name selector — process_modis_sds","text":"product character(1). Product code. custom_sel character(1). Custom filter. value NULL, preset filter overridden.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_sds.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Selected MODIS sinusoidal grid product subdataset name selector — process_modis_sds","text":"character object conforms regular expression. Details regular expression R can found regexp.","code":""},{"path":[]},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_sds.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Selected MODIS sinusoidal grid product subdataset name selector — process_modis_sds","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_swath.html","id":null,"dir":"Reference","previous_headings":"","what":"Mosaic MODIS swaths — process_modis_swath","title":"Mosaic MODIS swaths — process_modis_swath","text":"function return SpatRaster object values selected subdatasets. Swath data include curvilinear grids, require warping/rectifying original curvilinear grids rectilinear grids. function internally warps inputs mosaic warped images one large SpatRaster object. Users need select subdataset process. full path looks like \"HDF4_EOS:EOS_SWATH:{file_path}:mod06:subdataset\", file_path full path hdf file.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_swath.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Mosaic MODIS swaths — process_modis_swath","text":"","code":"process_modis_swath( path = NULL, date = NULL, subdataset = c(\"Cloud_Fraction_Day\", \"Cloud_Fraction_Night\"), suffix = \":mod06:\", resolution = 0.025, ... )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_swath.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Mosaic MODIS swaths — process_modis_swath","text":"path character. Full paths hdf files. date character(1). Date query. subdataset character. One \"Cloud_Fraction_Day\" \"Cloud_Fraction_Night\" (available MOD06_L2) suffix character(1). formatted :{product}:, e.g., :mod06: resolution numeric(1). Resolution output raster. Unit degree. ... internal use.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_swath.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Mosaic MODIS swaths — process_modis_swath","text":"SpatRaster object. CRS \"EPSG:4326\".","code":""},{"path":[]},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_swath.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Mosaic MODIS swaths — process_modis_swath","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_warp.html","id":null,"dir":"Reference","previous_headings":"","what":"Warp MODIS swath data into rectilinear grid raster — process_modis_warp","title":"Warp MODIS swath data into rectilinear grid raster — process_modis_warp","text":"Swath data type MODIS data, curvilinear points stored varying resolution depending relative position sensor axis. type data typically work well planar spatial data, users warp rectify data rectilinear raster. Main procedure done stars::st_warp, users able customize threshold fill potential gaps appear target resolution finer local resolution curvilinear grid points.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_warp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Warp MODIS swath data into rectilinear grid raster — process_modis_warp","text":"","code":"process_modis_warp( path = NULL, cellsize = 0.25, threshold = 0.5, crs = 4326, ... )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_warp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Warp MODIS swath data into rectilinear grid raster — process_modis_warp","text":"path File path MODIS swath exact sub-dataset specification. cellsize numeric(1). Cell size (spatial resolution) output rectilinear grid raster. threshold numeric(1). Maximum distance fill gaps occur. crs integer(1)/character(1). Coordinate system definition. compatible EPSG codes WKT2. See terra::crs sf::st_crs / EPSG ... internal use.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_warp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Warp MODIS swath data into rectilinear grid raster — process_modis_warp","text":"stars object.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_warp.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Warp MODIS swath data into rectilinear grid raster — process_modis_warp","text":"Users specify sub-dataset flags compatible gdalinfo","code":""},{"path":[]},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_modis_warp.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Warp MODIS swath data into rectilinear grid raster — process_modis_warp","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_narr.html","id":null,"dir":"Reference","previous_headings":"","what":"Import and clean NOAA NCEP North American Regional Reanalysis (NARR) data\ndownloaded with download_narr or download_data(dataset_name = ","title":"Import and clean NOAA NCEP North American Regional Reanalysis (NARR) data\ndownloaded with download_narr or download_data(dataset_name = ","text":"Import clean NOAA NCEP North American Regional Reanalysis (NARR) data downloaded download_narr download_data(dataset_name = \"NARR\"). Function returns SpatRast object containing user-defined variable interest. Layer names indicate variable, pressure level, date (YYYYMMDD).","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_narr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import and clean NOAA NCEP North American Regional Reanalysis (NARR) data\ndownloaded with download_narr or download_data(dataset_name = ","text":"","code":"process_narr( date = c(\"2023-09-01\", \"2023-09-01\"), variable = NULL, path = NULL )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_narr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import and clean NOAA NCEP North American Regional Reanalysis (NARR) data\ndownloaded with download_narr or download_data(dataset_name = ","text":"date character(2). length 10 . Format \"YYYY-MM-DD\". variable character(1). NARR variable name(s). path character(1). Directory downloaded GEOS-CF netCDF files.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_narr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import and clean NOAA NCEP North American Regional Reanalysis (NARR) data\ndownloaded with download_narr or download_data(dataset_name = ","text":"SpatRaster object","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_narr.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Import and clean NOAA NCEP North American Regional Reanalysis (NARR) data\ndownloaded with download_narr or download_data(dataset_name = ","text":"Mitchell Manware","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_nei.html","id":null,"dir":"Reference","previous_headings":"","what":"Prepare National Emission Inventory CSV files — process_nei","title":"Prepare National Emission Inventory CSV files — process_nei","text":"NEI data comprises multiple csv files emissions 50+ pollutants recorded county level. raw data files, function join combined table NEI data county boundary, perform spatial join target locations.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_nei.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prepare National Emission Inventory CSV files — process_nei","text":"","code":"process_nei(path = NULL, county = NULL, year = c(2017, 2020))"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_nei.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prepare National Emission Inventory CSV files — process_nei","text":"path character(1). Directory NEI csv files. county SpatVector/sf. County boundaries. year integer(1) Year use. Currently 2017 2020 accepted.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_nei.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prepare National Emission Inventory CSV files — process_nei","text":"SpatVector object.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_nei.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Prepare National Emission Inventory CSV files — process_nei","text":"Base files county argument can downloaded directly U.S. Census Bureau using tigris package. function reproject census boundaries. Users aware coordinate system census boundary data analyses.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_nei.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Prepare National Emission Inventory CSV files — process_nei","text":"Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_nlcd.html","id":null,"dir":"Reference","previous_headings":"","what":"Process raw National Landuse Classification Dataset — process_nlcd","title":"Process raw National Landuse Classification Dataset — process_nlcd","text":"Reads NLCD file selected year.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_nlcd.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Process raw National Landuse Classification Dataset — process_nlcd","text":"","code":"process_nlcd(path = NULL, year = 2021)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_nlcd.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Process raw National Landuse Classification Dataset — process_nlcd","text":"path character giving nlcd data path year numeric giving year NLCD data used","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_nlcd.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Process raw National Landuse Classification Dataset — process_nlcd","text":"SpatRaster object.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_nlcd.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Process raw National Landuse Classification Dataset — process_nlcd","text":"Eva Marques, Insang Song","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_sedac_codes.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate resolution codes based on NASA SEDAC population resolution. — process_sedac_codes","title":"Generate resolution codes based on NASA SEDAC population resolution. — process_sedac_codes","text":"Generate resolution codes based NASA SEDAC population resolution.","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_sedac_codes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate resolution codes based on NASA SEDAC population resolution. — process_sedac_codes","text":"","code":"process_sedac_codes(string, invert = FALSE)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/process_sedac_codes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate resolution codes based on NASA SEDAC population resolution. — process_sedac_codes","text":"string character(1). 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sftime object SpatRaster /!\\ can time consuming sftime spatially structured","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/sftime_as_spatraster.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert sftime object to SpatRaster\n/!\\ can be very time consuming if sftime is not spatially structured — sftime_as_spatraster","text":"","code":"sftime_as_spatraster(x, varname)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/sftime_as_spatraster.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert sftime object to SpatRaster\n/!\\ can be very time consuming if sftime is not spatially structured — sftime_as_spatraster","text":"x sftime varname variable rasterize","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/sftime_as_spatraster.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert sftime object to SpatRaster\n/!\\ can be very time consuming if sftime is not spatially structured — sftime_as_spatraster","text":"SpatRaster layers corresponding timestamps","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/sftime_as_spatraster.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Convert sftime object to SpatRaster\n/!\\ can be very time consuming if sftime is not spatially structured — sftime_as_spatraster","text":"Eva Marques","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/sftime_as_spatrds.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert sftime object to SpatVectorDataset\n/!\\ running time can be 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be very long if x is not\nspatially and temporally structured — sftime_as_spatrds","text":"x sftime","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/sftime_as_spatrds.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Convert sftime object to SpatVectorDataset\n/!\\ running time can be very long if x is not\nspatially and temporally structured — sftime_as_spatrds","text":"Eva Marques","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/sftime_as_spatvector.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert sftime object to SpatVector — sftime_as_spatvector","title":"Convert sftime object to SpatVector — sftime_as_spatvector","text":"Convert sftime object SpatVector","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/sftime_as_spatvector.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert sftime object to SpatVector — sftime_as_spatvector","text":"","code":"sftime_as_spatvector(x)"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/sftime_as_spatvector.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert sftime object to SpatVector — sftime_as_spatvector","text":"x sftime","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/sftime_as_spatvector.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert sftime object to SpatVector — sftime_as_spatvector","text":"terra::SpatVector","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/sftime_as_spatvector.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Convert sftime object to SpatVector — sftime_as_spatvector","text":"Eva Marques","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/spatraster_as_sftime.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a sftime from a terra::SpatRaster — spatraster_as_sftime","title":"Create a sftime from a terra::SpatRaster — spatraster_as_sftime","text":"Create sftime terra::SpatRaster","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/spatraster_as_sftime.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a sftime from a terra::SpatRaster — spatraster_as_sftime","text":"","code":"spatraster_as_sftime(x, varname, timename = \"time\")"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/spatraster_as_sftime.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a sftime from a terra::SpatRaster — spatraster_as_sftime","text":"x terra::SpatRaster varname character variable column name sftime timename character time column name sftime (default: \"time\")","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/spatraster_as_sftime.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a sftime from a terra::SpatRaster — spatraster_as_sftime","text":"sftime object","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/spatraster_as_sftime.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Create a sftime from a terra::SpatRaster — spatraster_as_sftime","text":"Eva Marques","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/spatrds_as_sftime.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a sftime from a terra::SpatRasterDataset — spatrds_as_sftime","title":"Create a sftime from a terra::SpatRasterDataset — spatrds_as_sftime","text":"Create sftime terra::SpatRasterDataset","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/spatrds_as_sftime.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a sftime from a terra::SpatRasterDataset — spatrds_as_sftime","text":"","code":"spatrds_as_sftime(x, timename = \"time\")"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/spatrds_as_sftime.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a sftime from a terra::SpatRasterDataset — spatrds_as_sftime","text":"x terra::SpatRasterDataset (~ list named SpatRasters) timename character time column name sftime (default: \"time\")","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/spatrds_as_sftime.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a sftime from a terra::SpatRasterDataset — spatrds_as_sftime","text":"sftime object","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/spatrds_as_sftime.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Create a sftime from a terra::SpatRasterDataset — spatrds_as_sftime","text":"Eva Marques","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/spatvector_as_sftime.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a sftime from a terra::SpatVector — spatvector_as_sftime","title":"Create a sftime from a terra::SpatVector — spatvector_as_sftime","text":"Create sftime terra::SpatVector","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/spatvector_as_sftime.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a sftime from a terra::SpatVector — spatvector_as_sftime","text":"","code":"spatvector_as_sftime(x, timename = \"time\")"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/spatvector_as_sftime.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a sftime from a terra::SpatVector — spatvector_as_sftime","text":"x terra::SpatVector timename character time column name x (default: \"time\")","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/spatvector_as_sftime.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a sftime from a terra::SpatVector — spatvector_as_sftime","text":"sftime object","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/spatvector_as_sftime.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Create a sftime from a terra::SpatVector — spatvector_as_sftime","text":"Eva Marques","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/test_download_functions.html","id":null,"dir":"Reference","previous_headings":"","what":"Apply download function-specific unit tests — test_download_functions","title":"Apply download function-specific unit tests — test_download_functions","text":"Apply download function-specific unit tests","code":""},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/test_download_functions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Apply download function-specific unit tests — test_download_functions","text":"","code":"test_download_functions( directory_to_download = NULL, directory_to_save = directory_to_save, commands_path = commands_path, url_status = url_status )"},{"path":"https://spatiotemporal-exposures-and-toxicology.github.io/amadeus/reference/test_download_functions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Apply download function-specific unit tests — test_download_functions","text":"directory_to_download directory test download directory_to_save directory test saving commands_path file path download commands url_status logical vector URL status = 200","code":""}]
+[{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"motivation","dir":"Articles","previous_headings":"","what":"Motivation","title":"download_data() and NASA EarthData Account","text":"data_download() function developed improve researchers’ access publicly available geospatial data sets. Although data already available online, using web browser manually download hundreds thousands data files slow, arduous, (efficiently) repeatable. Additionally, users may familiar creating download recipes Bash (Unix shell), data_download() allows researchers download data directly R, common coding language field environmental health research. Finally, function-izing data downloads useful repeated code automated analysis pipelines.","code":""},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"data_download","dir":"Articles","previous_headings":"","what":"data_download()","title":"download_data() and NASA EarthData Account","text":"data_download() capable accessing downloading geospatial data sets, collections, variables variety sources. wrapper function calls source-specific data download functions, utilizing unique combination input parameters, host URL, naming convention, data formats. Source-Specific Download Functions Sources important note data_download() calls source-specific function based dataset_name = parameter. Using source-specific function directly return exact data (parameters ), data_download() may beneficial using loop download data various sources. example, download_data(dataset_name = \"hms\", ...) return data download_hms_data(...) assuming ... indicates parameters.","code":""},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"parameters","dir":"Articles","previous_headings":"data_download()","what":"Parameters","title":"download_data() and NASA EarthData Account","text":"User-defined parameters differ based data source. Required parameters source can checked names(formals()). two functions different required parameters download_hms_data() uses daily temporal resolution download_narr_monolevel_data() uses yearly, share common, standard parameters.","code":"names(formals(download_hms_data)) ## [1] \"date_start\" \"date_end\" ## [3] \"data_format\" \"directory_to_download\" ## [5] \"directory_to_save\" \"data_download_acknowledgement\" ## [7] \"download\" \"remove_command\" ## [9] \"unzip\" \"remove_zip\" names(formals(download_narr_monolevel_data)) ## [1] \"year_start\" \"year_end\" ## [3] \"variables\" \"directory_to_save\" ## [5] \"data_download_acknowledgement\" \"download\" ## [7] \"remove_command\""},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"standard-parameters","dir":"Articles","previous_headings":"data_download() > Parameters","what":"Standard parameters","title":"download_data() and NASA EarthData Account","text":"Four parameters included data download functions. Additionally, dataset_name = parameter must specified using data_download(), assumed using source-specific download function.","code":""},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"function-structure","dir":"Articles","previous_headings":"data_download()","what":"Function Structure","title":"download_data() and NASA EarthData Account","text":"Although source-specific download function unique, follow general structure. following chunks code adopted download_hms_data() demonstrate functions’ structure. 1. Clean Parameters 2. Generate Download URLs 3. Generate download file names 4. Initiate “…commands.txt” 5. Concatenate download commands 6. Finalize “…commands.txt” 7. Run commands “…commands.txt” 8. Zip files (applicable)","code":""},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"clean-parameters","dir":"Articles","previous_headings":"data_download() > Function Structure","what":"1. Clean parameters","title":"download_data() and NASA EarthData Account","text":"Cleaning user-defined parameters highly dependent parameters desired URL created. common parameter cleaning step creating date-time sequence based given temporal range required format, case YYYYMMDD.","code":"# user defined parameters date_start <- \"2023-12-28\" date_end <- \"2024-01-02\" date_sequence <- seq( as.Date(date_start, format = \"%Y-%m-%d\"), as.Date(date_end, format = \"%Y-%m-%d\"), \"day\" ) date_sequence <- gsub(\"-\", \"\", as.character(date_sequence)) date_sequence ## [1] \"20231228\" \"20231229\" \"20231230\" \"20231231\" \"20240101\" \"20240102\""},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"generate-download-urls","dir":"Articles","previous_headings":"data_download() > Function Structure","what":"2. Generate download URLs","title":"download_data() and NASA EarthData Account","text":"URL base pattern identified manually inspecting download link source-specific web page. download_hms_data() utilizes year, month, date, data format generate download url. download URL created date date_sequence based fixed pattern.","code":"# user defined parameters data_format <- \"Shapefile\" suffix <- \".zip\" urls <- NULL for (d in seq_along(date_sequence)) { year <- substr(date_sequence[d], 1, 4) month <- substr(date_sequence[d], 5, 6) base <- \"https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/\" url <- paste0( base, data_format, \"/\", year, \"/\", month, \"/hms_smoke\", date_sequence[d], suffix ) urls <- c(urls, url) } urls ## [1] \"https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/2023/12/hms_smoke20231228.zip\" ## [2] \"https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/2023/12/hms_smoke20231229.zip\" ## [3] \"https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/2023/12/hms_smoke20231230.zip\" ## [4] \"https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/2023/12/hms_smoke20231231.zip\" ## [5] \"https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/2024/01/hms_smoke20240101.zip\" ## [6] \"https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/2024/01/hms_smoke20240102.zip\""},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"generate-download-file-names","dir":"Articles","previous_headings":"data_download() > Function Structure","what":"3. Generate download file names","title":"download_data() and NASA EarthData Account","text":"generation download file names also follows fixed pattern, typically combination user-defined download directory, data set name, spatiotemporal characteristic, data type, , applicable, specific variable name. Unlike download URLs, download file names can defined way writer function, using previously defined characteristics useful identification. download URL created date date_sequence based fixed pattern.","code":"# user defined parameters directory_to_download <- \"./data/\" download_file_names <- NULL for (d in seq_along(date_sequence)) { download_file_name <- paste0( directory_to_download, \"hms_smoke_\", data_format, \"_\", date_sequence[d], suffix ) download_file_names <- c(download_file_names, download_file_name) } download_file_names ## [1] \"./data/hms_smoke_Shapefile_20231228.zip\" ## [2] \"./data/hms_smoke_Shapefile_20231229.zip\" ## [3] \"./data/hms_smoke_Shapefile_20231230.zip\" ## [4] \"./data/hms_smoke_Shapefile_20231231.zip\" ## [5] \"./data/hms_smoke_Shapefile_20240101.zip\" ## [6] \"./data/hms_smoke_Shapefile_20240102.zip\""},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"initiate-commands-txt","dir":"Articles","previous_headings":"data_download() > Function Structure","what":"4. Initiate “…commands.txt”","title":"download_data() and NASA EarthData Account","text":"important aspect data download function sink()...cat()...sink() structure. Rather using utils::download.file() function, text file created store download commands generated URLs file names. structure utilized several reasons: Consistent structure source-specific download functions. download.file() function accept vectors URLs destination files downloading. additional loop download data increase function complexity may reduce performance. Writing commands Bash (Unix shell) script allows specific arguments flags. Storing download URLs without immediately running download allows unit testing URL checking (Unit Tests). text file containing download commands named based data set, temporal range, data transfer method. Create sink text file.","code":"commands_txt <- paste0( directory_to_download, \"hms_smoke_\", head(date_sequence, n = 1), \"_\", tail(date_sequence, n = 1), \"_curl_commands.txt\" ) sink(commands_txt)"},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"concatenate-download-commands","dir":"Articles","previous_headings":"data_download() > Function Structure","what":"5. Concatenate download commands","title":"download_data() and NASA EarthData Account","text":"Linux-based download commands written according data transfer method, download URL, download file name, additional arguments. additional arguments included, order, depend data transfer method URL type. information curl wget, two data transfer methods utilized data download functions, see curl.1 man page GNU Wget 1.21.1-dirty Manual (latest version January 8, 2024). cat() function store download commands written loop previously sunk commands text file (commands_txt).","code":"for (d in seq_along(date_sequence)) { download_comamnd <- paste0( \"curl -s -o \", download_file_names[d], \" --url \", urls[d], \"\\n\" ) cat(download_comamnd) }"},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"finalize-commands-txt","dir":"Articles","previous_headings":"data_download() > Function Structure","what":"6. Finalize “…commands.txt”","title":"download_data() and NASA EarthData Account","text":"download commands concatenated commands text file, second sink() command run finalize file stop appending R output.","code":"sink()"},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"run-commands-in-commands-txt","dir":"Articles","previous_headings":"data_download() > Function Structure","what":"7. Run commands in “…commands.txt”","title":"download_data() and NASA EarthData Account","text":"“system command” must created run download commands stored commands text file. bash script, . indicates run commands within given script. case, run commands within commands text file. Running system_command deploys “helper function”, download_run(), function created reduce repeated code across source-specific download functions. function takes two parameters, system_command =, indicates command run, download =, user-defined logical parameter. data download initiated running download_run() system command identified download = TRUE. Checking download directory shows requested files downloaded.","code":"system_command <- paste0( \". \", commands_txt, \"\\n\" ) system_command ## [1] \". ./data/hms_smoke_20231228_20240102_curl_commands.txt\\n\" download_run <- function( download = FALSE, system_command = NULL) { if (download == TRUE) { cat(paste0(\"Downloading requested files...\\n\")) system(command = system_command) cat(paste0(\"Requested files have been downloaded.\\n\")) } else { cat(paste0(\"Skipping data download.\\n\")) return(NULL) } } download_run( download = TRUE, system_command = system_command ) list.files(path = directory_to_download) ## [1] \"hms_smoke_Shapefile_20231228.zip\" \"hms_smoke_Shapefile_20231229.zip\" ## [3] \"hms_smoke_Shapefile_20231230.zip\" \"hms_smoke_Shapefile_20231231.zip\" ## [5] \"hms_smoke_Shapefile_20240101.zip\" \"hms_smoke_Shapefile_20240102.zip\""},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"zip-files-if-applicable","dir":"Articles","previous_headings":"data_download() > Function Structure","what":"8. Zip files (if applicable)","title":"download_data() and NASA EarthData Account","text":"source-specific data download functions follow general pattern, functions download zip files require additional steps inflate remove downloaded zip files, desired. two steps run helper functions, run user-defined unzip = remove_zip = parameters data_download(). download_unzip() inflates zip files unzip = TRUE, skips inflation unzip = FALSE. download_remove_zips() removes downloaded zip files remove = TRUE, skips removal remove = FALSE. demonstration unzip (inflate) downloaded zip files delete . Listing files shows contents zip files inflated zip files retained. download function structured successfully.","code":"download_unzip <- function(file_name, directory_to_unzip, unzip = TRUE) { if (!unzip) { cat(paste0(\"Downloaded files will not be unzipped.\\n\")) return(NULL) } cat(paste0(\"Unzipping files...\\n\")) unzip(file_name, exdir = directory_to_unzip ) cat(paste0( \"Files unzipped and saved in \", directory_to_unzip, \".\\n\" )) } download_remove_zips <- function(remove = FALSE, download_name) { if (remove) { cat(paste0(\"Removing download files...\\n\")) file.remove(download_name) cat(paste0(\"Download files removed.\\n\")) } } for (f in seq_along(download_file_names)) { download_unzip( file_name = download_file_names[f], directory_to_unzip = directory_to_download, unzip = TRUE ) } download_remove_zips( download_name = download_file_names, remove = FALSE ) ## Unzipping files... ## Files unzipped and saved in ./data/. ## Unzipping files... ## Files unzipped and saved in ./data/. ## Unzipping files... ## Files unzipped and saved in ./data/. ## Unzipping files... ## Files unzipped and saved in ./data/. ## Unzipping files... ## Files unzipped and saved in ./data/. ## Unzipping files... ## Files unzipped and saved in ./data/. list.files(path = directory_to_download) ## [1] \"hms_smoke_Shapefile_20231228.zip\" \"hms_smoke_Shapefile_20231229.zip\" ## [3] \"hms_smoke_Shapefile_20231230.zip\" \"hms_smoke_Shapefile_20231231.zip\" ## [5] \"hms_smoke_Shapefile_20240101.zip\" \"hms_smoke_Shapefile_20240102.zip\" ## [7] \"hms_smoke20231228.dbf\" \"hms_smoke20231228.prj\" ## [9] \"hms_smoke20231228.shp\" \"hms_smoke20231228.shx\" ## [11] \"hms_smoke20231229.dbf\" \"hms_smoke20231229.prj\" ## [13] \"hms_smoke20231229.shp\" \"hms_smoke20231229.shx\" ## [15] \"hms_smoke20231230.dbf\" \"hms_smoke20231230.prj\" ## [17] \"hms_smoke20231230.shp\" \"hms_smoke20231230.shx\" ## [19] \"hms_smoke20231231.dbf\" \"hms_smoke20231231.prj\" ## [21] \"hms_smoke20231231.shp\" \"hms_smoke20231231.shx\" ## [23] \"hms_smoke20240101.dbf\" \"hms_smoke20240101.prj\" ## [25] \"hms_smoke20240101.shp\" \"hms_smoke20240101.shx\" ## [27] \"hms_smoke20240102.dbf\" \"hms_smoke20240102.prj\" ## [29] \"hms_smoke20240102.shp\" \"hms_smoke20240102.shx\""},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"unit-tests","dir":"Articles","previous_headings":"","what":"Unit Tests","title":"download_data() and NASA EarthData Account","text":"previous outline successfully cleaned parameters, generated URLs, downloaded data, can sure continue work different temporal ranges data types? end, unit tests implemented ensure data download function runs properly URLs produced 2. Generate download URLs valid accessible. Like download functions, unit tests rely “helper” functions reduce repeated code across tests.","code":""},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"helper-functions","dir":"Articles","previous_headings":"Unit Tests","what":"Helper functions","title":"download_data() and NASA EarthData Account","text":"read_commands() imports commands text file converts data frame vector. extract_urls() extracts download URL vector commands. position = URL within download command determined 5. Concatenate download commands. check_url_status() important download test “helper” functions. function utilizes httr::HEAD() httr::GET() check HTTP response status given URL. desired HTTP response status 200, means URL valid accessible. check_url_status() returns logical value indicate whether URL returns HTTP status 200 (TRUE) (FALSE). information HTTP status’, see HTTP response status codes. check_urls() applies check_url_status() random sample URLs extracted extract_urls(). sample size vary based data set spatio-temporal parameters tested. function returns logical vector containing output check_url_status().","code":"read_commands <- function( commands_path = commands_path) { commands <- utils::read.csv(commands_path, header = FALSE) commands <- commands[seq_len(nrow(commands)), ] return(commands) } # function to extract URLs from vector extract_urls <- function( commands = commands, position = NULL) { if (is.null(position)) { cat(paste0(\"URL position in command is not defined.\\n\")) return(NULL) } url_list <- NULL for (c in seq_along(commands)) { url <- stringr::str_split_i(commands[c], \" \", position) url_list <- c(url_list, url) } return(url_list) } check_url_status <- function( url, method = \"HEAD\") { http_status_ok <- 200 if (method == \"HEAD\") { hd <- httr::HEAD(url) } else if (method == \"GET\") { hd <- httr::GET(url) } status <- hd$status_code return(status == http_status_ok) } check_urls <- function( urls = urls, size = NULL, method = \"HEAD\") { if (is.null(size)) { cat(paste0(\"URL sample size is not defined.\\n\")) return(NULL) } if (length(urls) < size) { size <- length(urls) } url_sample <- sample(urls, size, replace = FALSE) url_status <- sapply(url_sample, check_url_status, method = method ) return(url_status) }"},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"testthat","dir":"Articles","previous_headings":"Unit Tests","what":"testthat","title":"download_data() and NASA EarthData Account","text":"demonstrate test action, test URLs generated download_data() NOAA HMS Smoke data set. information see testthat. Although testthat::test_that(...) chunk contains 32 lines code, unit test performed expect_true((url_status)). words, line expecting (expect_true()) (()) sampled URLs return HTTP response status 200 (url_status). Since expectation met, test passed! alternate example, can use start end date known data. URLs associated dates exist, expect function fail. test utilizes expect_error() data_download() wrapper function returns error message underlying source-specific download function returns error. test utilizes expect_error() data_download() wrapper function returns error message underlying source-specific download function returns error. directly used download_hms_data function, expect receive error. expected, test passes NOAA HMS Smoke data set contain data January 1-2, 1800. unit tests just two many implemented download_data() accompanying source-specific download functions, demonstrate unit testing helps build stable code.","code":"library(testthat) testthat::test_that( \"Valid dates return HTTP response status = 200.\", { # parameters test_start <- \"2023-12-28\" test_end <- \"2024-01-02\" test_directory <- \"./data\" # download download_data( dataset_name = \"noaa\", date_start = test_start, date_end = test_end, data_format = \"Shapefile\", directory_to_download = test_directory, directory_to_save = test_directory, data_download_acknowledgement = TRUE, download = FALSE, remove_command = FALSE, unzip = FALSE, remove_zip = FALSE ) commands_path <- paste0( test_directory, \"hms_smoke_\", gsub(\"-\", \"\", test_start), \"_\", gsub(\"-\", \"\", test_end), \"_curl_commands.txt\" ) # helpers commands <- read_commands(commands_path = commands_path) urls <- extract_urls(commands = commands, position = 6) url_status <- check_urls(urls = urls, size = 6, method = \"HEAD\") # test for true expect_true(all(url_status)) } ) ## Skipping data download. ## Downloaded files will not be unzipped. ## Downloaded files will not be unzipped. ## Downloaded files will not be unzipped. ## Downloaded files will not be unzipped. ## Downloaded files will not be unzipped. ## Downloaded files will not be unzipped. ## Test passed 🥳 testthat::test_that( \"Invalid dates cause function to fail.\", { # parameters test_start <- \"1800-01-01\" test_end <- \"1800-01-02\" test_directory <- \"../inst/extdata/\" # test for error testthat::expect_error( download_data( dataset_name = \"noaa\", date_start = test_start, date_end = test_end, data_format = \"Shapefile\", directory_to_download = test_directory, directory_to_save = test_directory, data_download_acknowledgement = TRUE, download = FALSE, remove_command = FALSE, unzip = FALSE, remove_zip = FALSE ) ) } ) ## ## function (date_start = \"2023-09-01\", date_end = \"2023-09-01\", ## data_format = \"Shapefile\", directory_to_download = NULL, ## directory_to_save = NULL, data_download_acknowledgement = FALSE, ## download = FALSE, remove_command = FALSE, unzip = TRUE, remove_zip = FALSE) ## NULL ## Test passed 🥇 testthat::test_that( \"Invalid dates cause function to fail.\", { # parameters test_start <- \"1800-01-01\" test_end <- \"1800-01-02\" test_directory <- \"../inst/extdata/\" # test for error testthat::expect_error( download_hms_data( date_start = test_start, date_end = test_end, data_format = \"Shapefile\", directory_to_download = test_directory, directory_to_save = test_directory, data_download_acknowledgement = TRUE, download = FALSE, remove_command = FALSE, unzip = FALSE, remove_zip = FALSE ) ) } ) ## Test passed 🎉"},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"download-example","dir":"Articles","previous_headings":"","what":"Download Example","title":"download_data() and NASA EarthData Account","text":"function structure outlined unit tests place, can now perform data download. begin, check parameters required source-specific data download function. Define parameters. Download data. Checking directory shows desired data downloaded inflated, original zip files retained.","code":"names(formals(download_hms_data)) ## [1] \"date_start\" \"date_end\" ## [3] \"data_format\" \"directory_to_download\" ## [5] \"directory_to_save\" \"data_download_acknowledgement\" ## [7] \"download\" \"remove_command\" ## [9] \"unzip\" \"remove_zip\" date_start <- \"2023-12-28\" date_end <- \"2024-01-02\" data_format <- \"Shapefile\" data_directory <- \"./download_example/\" data_download_acknowledgement <- TRUE download <- TRUE # run data download remove_command <- TRUE # delete \"...commands.txt\" file unzip <- TRUE # inflate (unzip) downloaded zip files remove_zip <- FALSE # retain downloaded zip files download_data( dataset_name = \"hms\", date_start = date_start, date_end = date_end, directory_to_download = data_directory, directory_to_save = data_directory, data_download_acknowledgement = data_download_acknowledgement, download = download, remove_command = remove_command, unzip = unzip, remove_zip = remove_zip ) ## Downloading requested files... ## Requested files have been downloaded. ## Unzipping files... ## Files unzipped and saved in ./download_example/. ## Unzipping files... ## Files unzipped and saved in ./download_example/. ## Unzipping files... ## Files unzipped and saved in ./download_example/. ## Unzipping files... ## Files unzipped and saved in ./download_example/. ## Unzipping files... ## Files unzipped and saved in ./download_example/. ## Unzipping files... ## Files unzipped and saved in ./download_example/. list.files(data_directory) ## [1] \"hms_smoke_Shapefile_20231228.zip\" \"hms_smoke_Shapefile_20231229.zip\" ## [3] \"hms_smoke_Shapefile_20231230.zip\" \"hms_smoke_Shapefile_20231231.zip\" ## [5] \"hms_smoke_Shapefile_20240101.zip\" \"hms_smoke_Shapefile_20240102.zip\" ## [7] \"hms_smoke20231228.dbf\" \"hms_smoke20231228.prj\" ## [9] \"hms_smoke20231228.shp\" \"hms_smoke20231228.shx\" ## [11] \"hms_smoke20231229.dbf\" \"hms_smoke20231229.prj\" ## [13] \"hms_smoke20231229.shp\" \"hms_smoke20231229.shx\" ## [15] \"hms_smoke20231230.dbf\" \"hms_smoke20231230.prj\" ## [17] \"hms_smoke20231230.shp\" \"hms_smoke20231230.shx\" ## [19] \"hms_smoke20231231.dbf\" \"hms_smoke20231231.prj\" ## [21] \"hms_smoke20231231.shp\" \"hms_smoke20231231.shx\" ## [23] \"hms_smoke20240101.dbf\" \"hms_smoke20240101.prj\" ## [25] \"hms_smoke20240101.shp\" \"hms_smoke20240101.shx\" ## [27] \"hms_smoke20240102.dbf\" \"hms_smoke20240102.prj\" ## [29] \"hms_smoke20240102.shp\" \"hms_smoke20240102.shx\""},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"nasa-earthdata-account","dir":"Articles","previous_headings":"","what":"NASA EarthData Account","title":"download_data() and NASA EarthData Account","text":"mentioned Motivation, data_download() provides access publicly available geospatial data. Although publicly available, NASA data sources require NASA EarthData Account. example, UN WPP-Adjusted population density data NASA Socioeconomic Data Applications Center (SEDAC) requires EarthData account. Without EarthData Account prerequisite files prepared, data download functions return error. downloaded file unzipped data downloaded properly.","code":"download_data( dataset_name = \"sedac_population\", year = \"2020\", data_format = \"GeoTIFF\", data_resolution = \"60 minute\", directory_to_download = \"./sedac_population/\", directory_to_save = \"./sedac_population\", data_download_acknowledgement = TRUE, download = TRUE, unzip = TRUE, remove_zip = FALSE, remove_command = TRUE ) ## Downloading requested files... ## Requested files have been downloaded. ## Unzipping files... ## ## Warning in unzip(file_name, exdir = directory_to_unzip): error 1 in extracting from zip file ## ## Files unzipped and saved in ./sedac_population/."},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"register-or-log-in","dir":"Articles","previous_headings":"NASA EarthData Account","what":"Register or log in","title":"download_data() and NASA EarthData Account","text":"Visit https://urs.earthdata.nasa.gov/ register log NASA EarthData account. Account registration provides access NASA’s Earth Observing System Data Information System (EOSDIS) twelve Distributed Active Archive Centers (DAAC), including: Alaska Satellite Facility (ASF) DAAC Atmospheric Science Data Center (ASDC) Crustal Dynamics Data Information System (CDDIS) Global Hydrometeorology Resource Center (GHRC) Goddard Earth Sciences Data Information Services Center (GES DISC) Land Processes DAAC (LP DAAC) Level 1 Atmosphere Archive Distribution System (LAADS) DAAC National Snow Ice Data Center (NSIDC) DAAC Oak Ridge National Laboratory (ORNL) DAAC Ocean Biology DAAC (OB.DAAC) Physical Oceanography DAAC (PO.DAAC) Socioeconomic Data Applications Center (SEDAC) See https://www.earthdata.nasa.gov/eosdis/daacs information.","code":""},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"approved-applications","dir":"Articles","previous_headings":"NASA EarthData Account","what":"Approved applications","title":"download_data() and NASA EarthData Account","text":"creating account, navigate “Profile”(https://urs.earthdata.nasa.gov/profile), “Applications > Authorized Apps”. “Authorized Apps” page specifies NASA EarthData applications can use login credentials. example, ensure authorization enabled “SEDAC Website”, “SEDAC Website (Alpha)”, “SEDAC Website (Beta)”.","code":""},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"prerequisite-files","dir":"Articles","previous_headings":"NASA EarthData Account","what":"Prerequisite files","title":"download_data() and NASA EarthData Account","text":"NASA EarthData Account required applications authorized use credentials, time create prerequisite files. Note steps produce prerequisite files specific, much code used adopted Generate Earthdata Prerequisite Files NASA GES DISC’s “-’s” webpage (link).","code":""},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"netrc","dir":"Articles","previous_headings":"NASA EarthData Account > Prerequisite files","what":".netrc","title":"download_data() and NASA EarthData Account","text":"following commands create .netrc file, contains NASA EarthData Account credentials. First, set working directory home directory. Setting working directory differs Mac/Linux Windows machines. Create file named .netrc file.create(). Open connection .netrc sink(). Write line machine urs... replacing YOUR_USERNAME YOUR_PASSWORD NASA EarthData username password, respectively. writing line, close connection sink() . Edit settings , owner file, can read write .netrc. , check ensure file created properly.","code":"if (.Platform$OS.type == \"unix\") { setwd(\"~/\") } else if (.Platform$OS.type == \"windows\") { setwd(\"C:/\") } file.create(\".netrc\") sink(\".netrc\") writeLines( \"machine urs.earthdata.nasa.gov login YOUR_USERNAME password YOUR_PASSWORD\" ) sink() system(\"chmod 0600 .netrc\") file.exists(\".netrc\") ## [1] TRUE readLines(\".netrc\") ## [1] \"machine urs.earthdata.nasa.gov login YOUR_USERNAME password YOUR_PASSWORD\""},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"urs_cookies","dir":"Articles","previous_headings":"NASA EarthData Account > Prerequisite files","what":".urs_cookies","title":"download_data() and NASA EarthData Account","text":"following commands create .urs_cookies file. First, set working directory home directory. Create file named .netrc file.create(). , check ensure file created properly.","code":"if (.Platform$OS.type == \"unix\") { setwd(\"~/\") } else if (.Platform$OS.type == \"windows\") { setwd(\"C:/\") } file.create(\".urs_cookies\") file.exists(\".urs_cookies\") ## [1] TRUE"},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"dodsrc","dir":"Articles","previous_headings":"NASA EarthData Account > Prerequisite files","what":".dodsrc","title":"download_data() and NASA EarthData Account","text":"following commands create .urs_cookies file. First, set working directory home directory. Create file named “.dodsrc” file.create() Open connection .dodsrc sink(). Write lines beginning HTTP., replacing YOUR_USERNAME YOUR_PASSWORD NASA EarthData username password, respectively. writing line, close connection sink() . , check ensure file created properly. working Windows machine, copy .dodsrc file project working directory. Replace YOUR_WORKING_DIRECTORY absolute path project working directory. important ensure commands, well username, password, home directory, typed without error, single problem files result failed download. files created correctly, UN WPP-Adjusted population density data NASA Socioeconomic Data Applications Center (SEDAC) downloaded unzipped without returning error.","code":"if (.Platform$OS.type == \"unix\") { setwd(\"~/\") } else if (.Platform$OS.type == \"windows\") { setwd(\"C:/\") } file.create(\".dodsrc\") sink(\".dodsrc\") writeLines( paste0( \"HTTP.NETRC=YOUR_HOME_DIRECTORY/.netrc\\n\", \"HTTP.COOKIE.JAR=YOUR_HOME_DIRECTORY/.urs_cookies\" ) ) sink() file.exists(\".dodsrc\") ## [1] TRUE readLines(\".dodsrc\") ## [1] \"HTTP.NETRC=YOUR_HOME_DIRECTORY/.netrc\" ## [2] \"HTTP.COOKIE.JAR=YOUR_HOME_DIRECTORY/.urs_cookies\" if (.Platform$OS.type == \"windows\") { file.copy( \"C:/.dodsrc\", \"YOUR_WORKING_DIRECTORY/.dodsrc\" ) } download_data( dataset_name = \"sedac_population\", year = \"2020\", data_format = \"GeoTIFF\", data_resolution = \"60 minute\", directory_to_download = \"./sedac_population/\", directory_to_save = \"./sedac_population\", data_download_acknowledgement = TRUE, download = TRUE, unzip = TRUE, remove_zip = FALSE, remove_command = TRUE ) ## Downloading requested files... ## Requested files have been downloaded. ## Unzipping files... ## Files unzipped and saved in ./sedac_population/. list.files(\"./sedac_population\") ## [1] \"gpw_v4_population_density_adjusted_to_2015_unwpp_country_totals_rev11_2020_1_deg_tif_readme.txt\" ## [2] \"gpw_v4_population_density_adjusted_to_2015_unwpp_country_totals_rev11_2020_1_deg_tif.zip\" ## [3] \"gpw_v4_population_density_adjusted_to_2015_unwpp_country_totals_rev11_2020_1_deg.tif\""},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"references","dir":"Articles","previous_headings":"","what":"References","title":"download_data() and NASA EarthData Account","text":"EOSDIS Distributed Active Archive Centers (DAAC). National Aeronautics Space Administration (NASA). Date accessed: January 3, 2024. https://www.earthdata.nasa.gov/eosdis/daacs. Generate Earthdata Prerequisite Files. National Aeronautics Space Administration (NASA). Date accessed: January 3, 2024. https://disc.gsfc.nasa.gov/information/howto?title=%20to%20Generate%20Earthdata%20Prerequisite%20Files.","code":""},{"path":"https://kyle-messier.github.io/amadeus/articles/download_functions.html","id":"code-example","dir":"Articles","previous_headings":"","what":"Code Example","title":"download_data() and NASA EarthData Account","text":"following entire R code used create download_hms_data().","code":"download_hms_data ## function (date_start = \"2023-09-01\", date_end = \"2023-09-01\", ## data_format = \"Shapefile\", directory_to_download = NULL, ## directory_to_save = NULL, data_download_acknowledgement = FALSE, ## download = FALSE, remove_command = FALSE, unzip = TRUE, remove_zip = FALSE) ## { ## download_permit(data_download_acknowledgement = data_download_acknowledgement) ## check_for_null_parameters(mget(ls())) ## download_setup_dir(directory_to_download) ## download_setup_dir(directory_to_save) ## directory_to_download <- download_sanitize_path(directory_to_download) ## directory_to_save <- download_sanitize_path(directory_to_save) ## if (unzip == FALSE && remove_zip == TRUE) { ## stop(paste0(\"Arguments unzip = FALSE and remove_zip = TRUE are not \", ## \"acceptable together. Please change one.\\n\")) ## } ## date_sequence <- generate_date_sequence(date_start, date_end, ## sub_hyphen = TRUE) ## base <- \"https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/\" ## commands_txt <- paste0(directory_to_download, \"hms_smoke_\", ## utils::head(date_sequence, n = 1), \"_\", utils::tail(date_sequence, ## n = 1), \"_curl_commands.txt\") ## download_sink(commands_txt) ## download_names <- NULL ## for (f in seq_along(date_sequence)) { ## year <- substr(date_sequence[f], 1, 4) ## month <- substr(date_sequence[f], 5, 6) ## if (data_format == \"Shapefile\") { ## suffix <- \".zip\" ## directory_to_cat <- directory_to_download ## } ## else if (data_format == \"KML\") { ## suffix <- \".kml\" ## directory_to_cat <- directory_to_save ## } ## url <- paste0(base, data_format, \"/\", year, \"/\", month, ## \"/hms_smoke\", date_sequence[f], suffix) ## if (f == 1) { ## if (!(check_url_status(url))) { ## sink() ## file.remove(commands_txt) ## stop(paste0(\"Invalid date returns HTTP code 404. \", ## \"Check `date_start` parameter.\\n\")) ## } ## } ## destfile <- paste0(directory_to_cat, \"hms_smoke_\", data_format, ## \"_\", date_sequence[f], suffix) ## download_names <- c(download_names, destfile) ## command <- paste0(\"curl -s -o \", destfile, \" --url \", ## url, \"\\n\") ## cat(command) ## } ## sink() ## system_command <- paste0(\". \", commands_txt, \"\\n\") ## download_run(download = download, system_command = system_command) ## download_remove_command(remove = remove_command, commands_txt = commands_txt) ## if (data_format == \"KML\") { ## return(cat(paste0(\"KML files cannot be unzipped.\\n\"))) ## } ## for (d in seq_along(download_names)) { ## download_unzip(file_name = download_names[d], directory_to_unzip = directory_to_save, ## unzip = unzip) ## } ## download_remove_zips(remove = remove_zip, download_name = download_names) ## } ## "},{"path":"https://kyle-messier.github.io/amadeus/articles/epa_download.html","id":"downloading-and-pre-processing-pre-generated-epa-aqs-data-from-their-website","dir":"Articles","previous_headings":"","what":"Downloading and pre-processing pre-generated EPA AQS data from their website","title":"Downloading EPA Daily Data","text":"script downloads pre-processed data EPA’s AQS data desired variable, year(s), temporal resolution. script also joins multiple years’ data single data frame, downloads file metadata monitors included dataset. first version script (August 2023) written download daily PM2.5 data period 2018-2022. Available datasets can found website https://aqs.epa.gov/aqsweb/airdata/download_files.html.","code":""},{"path":"https://kyle-messier.github.io/amadeus/articles/epa_download.html","id":"setting-up-for-data-download","dir":"Articles","previous_headings":"Downloading and pre-processing pre-generated EPA AQS data from their website","what":"1. Setting up for data download","title":"Downloading EPA Daily Data","text":"Specifying temporal resolution, parameter interest, year Create list file URLs Specify download folder desired name downloaded zip files","code":"resolution <- \"daily\" parameter_code <- 88101 # Parameter Code for PM2.5 local conditions startyear <- 2018 endyear <- 2022 file_urls <- sprintf( paste(\"https://aqs.epa.gov/aqsweb/airdata/\", resolution, \"_\", parameter_code, \"_%.0f.zip\", sep = \"\" ), startyear:endyear ) file_urls ## [1] \"https://aqs.epa.gov/aqsweb/airdata/daily_88101_2018.zip\" ## [2] \"https://aqs.epa.gov/aqsweb/airdata/daily_88101_2019.zip\" ## [3] \"https://aqs.epa.gov/aqsweb/airdata/daily_88101_2020.zip\" ## [4] \"https://aqs.epa.gov/aqsweb/airdata/daily_88101_2021.zip\" ## [5] \"https://aqs.epa.gov/aqsweb/airdata/daily_88101_2022.zip\" download_dir <- \"../input/aqs/\" download_names <- sprintf( paste(download_dir, \"download_output_%.0f.zip\", sep = \"\" ), startyear:endyear ) download_names ## [1] \"../input/aqs/download_output_2018.zip\" ## [2] \"../input/aqs/download_output_2019.zip\" ## [3] \"../input/aqs/download_output_2020.zip\" ## [4] \"../input/aqs/download_output_2021.zip\" ## [5] \"../input/aqs/download_output_2022.zip\""},{"path":"https://kyle-messier.github.io/amadeus/articles/epa_download.html","id":"downloading-data","dir":"Articles","previous_headings":"Downloading and pre-processing pre-generated EPA AQS data from their website","what":"2. Downloading data","title":"Downloading EPA Daily Data","text":"Download zip files website Construct string unzipped file names","code":"download.file(file_urls, download_names, method = \"libcurl\") csv_names <- sprintf( paste(download_dir, resolution, \"_\", parameter_code, \"_%.0f.csv\", sep = \"\" ), startyear:endyear )"},{"path":"https://kyle-messier.github.io/amadeus/articles/epa_download.html","id":"processing-data","dir":"Articles","previous_headings":"Downloading and pre-processing pre-generated EPA AQS data from their website","what":"3. Processing data","title":"Downloading EPA Daily Data","text":"Unzip read .csv files, process join one dataframe. unique site identifier “ID.Code” string structure State-County-Site-Parameter-POC","code":"for (n in seq_along(file_urls)) { # Unzips file to same folder it was downloaded to unzip(download_names[n], exdir = download_dir) # Read in dataframe print(paste(\"reading and processing file:\", csv_names[n], \"...\")) data <- read.csv(csv_names[n], stringsAsFactors = FALSE) # Make unique site identifier: State-County-Site-Parameter-POC data$ID.Code <- paste(data$State.Code, data$County.Code, data$Site.Num, data$Parameter.Code, data$POC, sep = \"-\" ) # Concatenate with other years if (n == 1) { data_all <- data } else { data_all <- rbind(data_all, data) } } ## [1] \"reading and processing file:../input/aqs/daily_88101_2018.csv...\" ## [1] \"reading and processing file:../input/aqs/daily_88101_2019.csv...\" ## [1] \"reading and processing file:../input/aqs/daily_88101_2020.csv...\" ## [1] \"reading and processing file:../input/aqs/daily_88101_2021.csv...\" ## [1] \"reading and processing file:../input/aqs/daily_88101_2022.csv...\""},{"path":"https://kyle-messier.github.io/amadeus/articles/epa_download.html","id":"downloading-monitor-metadata-file-and-filter-for-relevant-sites","dir":"Articles","previous_headings":"Downloading and pre-processing pre-generated EPA AQS data from their website","what":"4. Downloading monitor metadata file and filter for relevant sites","title":"Downloading EPA Daily Data","text":"Download monitors file Unzip read Create site identifier Filter monitors file include monitors csv","code":"destfile <- paste(download_dir, \"aqs_monitors.zip\", sep = \"\") download.file(\"https://aqs.epa.gov/aqsweb/airdata/aqs_monitors.zip\", destfile) unzip(destfile, exdir = download_dir) monitors <- read.csv(\"../input/aqs/aqs_monitors.csv\", stringsAsFactors = FALSE) # Convert from string to numeric to get rid of leading zeros, # the NAs introduced are from monitors in Canada with site number=\"CC\" monitors$State.Code <- as.numeric(monitors$State.Code) monitors$ID.Code <- paste(monitors$State.Code, monitors$County.Code, monitors$Site.Num, monitors$Parameter.Code, monitors$POC, sep = \"-\" ) monitors <- read.csv(\"../input/aqs/aqs_monitors.csv\", stringsAsFactors = FALSE ) monitors_filter <- monitors[which(monitors$ID.Code %in% data_all$ID.Code), ]"},{"path":"https://kyle-messier.github.io/amadeus/articles/epa_download.html","id":"uploading-data-to-desired-folder","dir":"Articles","previous_headings":"Downloading and pre-processing pre-generated EPA AQS data from their website","what":"5. Uploading data to desired folder","title":"Downloading EPA Daily Data","text":"","code":"savepath <- \"../input/aqs/\" write.csv(data_all, paste(savepath, resolution, \"_\", parameter_code, \"_\", startyear, \"-\", endyear, \".csv\", sep = \"\" )) write.csv(monitors_filter, paste(savepath, \"monitors_\", parameter_code, \"_\", startyear, \"-\", endyear, \".csv\", sep = \"\" ))"},{"path":"https://kyle-messier.github.io/amadeus/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Kyle Messier. Author, maintainer. Mitchell Manware. Author, contributor. Insang Song. Author, contributor. Eva Marques. Author, contributor. Mariana Alifa Kassien. Author, contributor. Ranadeep Daw. Author, contributor. Daniel Zilber. Author, contributor.","code":""},{"path":"https://kyle-messier.github.io/amadeus/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Messier K, Manware M, Song , Marques E, Alifa Kassien M, Daw R, Zilber D (2024). amadeus: AMADEUS: Mechanism/Machine Data, Environments, User Setup. R package version 0.1.3, , https://github.com/Spatiotemporal-Exposures--Toxicology/amadeus.","code":"@Manual{, title = {amadeus: AMADEUS: A Mechanism/Machine for Data, Environments, and User Setup}, author = {Kyle Messier and Mitchell Manware and Insang Song and Eva Marques and Mariana {Alifa Kassien} and Ranadeep Daw and Daniel Zilber}, year = {2024}, note = {R package version 0.1.3, }, url = {https://github.com/Spatiotemporal-Exposures-and-Toxicology/amadeus}, }"},{"path":"https://kyle-messier.github.io/amadeus/index.html","id":"amadeus","dir":"","previous_headings":"","what":"AMADEUS: A Mechanism/Machine for Data, Environments, and User Setup","title":"AMADEUS: A Mechanism/Machine for Data, Environments, and User Setup","text":"Mechanism/Machine Data, Environments, User Setup amadeus R package devloped improve expideite users’ access large, publicly available geospatial data sets. functions amadeus allow users download import cleaned geospatial data directly R, useful automated run scripts, analysis pipelines, reproducible science general.","code":""},{"path":"https://kyle-messier.github.io/amadeus/index.html","id":"download","dir":"","previous_headings":"","what":"Download","title":"AMADEUS: A Mechanism/Machine for Data, Environments, and User Setup","text":"download_data() accesses downloads raw geospatial data variety open source data repositories. function wrapper calls source-specific download functions, account source’s unique combination URL, file naming conventions, data types. Download functions cover following sources: See download_functions vignette detailed description source-specific download functions. Example use download_data() using NOAA NCEP North American Regional Reanalysis’s (NARR) “weasd” (Daily Accumulated Snow Surface) variable.","code":"> download_data( + dataset_name = \"narr_monolevel\", + year_start = 2022, + year_end = 2022, + variable = \"weasd\", + directory_to_save = directory_to_save, + data_download_acknowledgement = TRUE, + download = TRUE + ) Downloading requested files... Requested files have been downloaded. > list.files(paste0(directory_to_save, \"weasd/\")) [1] \"weasd.2022.nc\""},{"path":"https://kyle-messier.github.io/amadeus/index.html","id":"process","dir":"","previous_headings":"","what":"Process","title":"AMADEUS: A Mechanism/Machine for Data, Environments, and User Setup","text":"process() imports cleans raw geospatial data (downloaded download()), returns single SpatRaster SpatVector user’s R environment. process() “cleans” data defining interpretable layer names, ensuring coordinate reference system present, managing time data (applicable). avoid errors using process(), edit raw downloaded data files. Passing user-generated edited data procces() may result errors underlying functions adapted sources’ raw data file type. Example use process() using downloaded “weasd” data.","code":"> weasd <- process_narr( + date = c(\"2022-01-01\", \"2022-01-05\"), + variable = \"weasd\", + path = path + ) Cleaning weasd data for year 2022... Returning daily weasd data from 2022-01-01 to 2022-01-05. > weasd class : SpatRaster dimensions : 277, 349, 5 (nrow, ncol, nlyr) resolution : 32462.99, 32463 (x, y) extent : -16231.49, 11313351, -16231.5, 8976020 (xmin, xmax, ymin, ymax) coord. ref. : +proj=lcc +lat_0=50 +lon_0=-107 +lat_1=50 +lat_2=50 +x_0=5632642.22547 +y_0=4612545.65137 +datum=WGS84 +units=m +no_defs source : weasd.2022.nc:weasd varname : weasd (Daily Accumulated Snow at Surface) names : weasd_20220101, weasd_20220102, weasd_20220103, weasd_20220104, weasd_20220105 unit : kg/m^2, kg/m^2, kg/m^2, kg/m^2, kg/m^2 time : 2022-01-01 to 2022-01-05 UTC"},{"path":"https://kyle-messier.github.io/amadeus/index.html","id":"calculate-covariates","dir":"","previous_headings":"","what":"Calculate Covariates","title":"AMADEUS: A Mechanism/Machine for Data, Environments, and User Setup","text":"calc_covariates() stems beethoven package, air pollution model’s (citation) need various types data extracted precise locations. calc_covariates(), therefore, extracts data “cleaned” SpatRaster SpatVector object user defined locations. Users can choose buffer locations. function returns data.frame data extracted locations layer row SpatRaster SpatVector object, respectively. Example calc_covariates() using processed “weasd” data.","code":"> weasd_covar <- calc_narr( + from = weasd, + locs = locs, + locs_id = \"site_id\", + radius = 0 + ) Converting data.table to data.frame... Projecting data to desired coordinate reference system... Utilizing 0 meter buffer for covariate calculations. Calculating daily weasd covariates at monolevel for date 2022-01-01... Calculating daily weasd covariates at monolevel for date 2022-01-02... Calculating daily weasd covariates at monolevel for date 2022-01-03... Calculating daily weasd covariates at monolevel for date 2022-01-04... Calculating daily weasd covariates at monolevel for date 2022-01-05... Returning weasd covariates. > weasd_covar site_id date level weasd_0 1 37183001488101 2022-01-01 monolevel 0.000000000 2 37183002188101 2022-01-01 monolevel 0.000000000 3 37063001588101 2022-01-01 monolevel 0.000000000 4 37183001488101 2022-01-02 monolevel 0.000000000 5 37183002188101 2022-01-02 monolevel 0.000000000 6 37063001588101 2022-01-02 monolevel 0.000000000 7 37183001488101 2022-01-03 monolevel 0.000000000 8 37183002188101 2022-01-03 monolevel 0.000000000 9 37063001588101 2022-01-03 monolevel 0.000000000 10 37183001488101 2022-01-04 monolevel 0.000000000 11 37183002188101 2022-01-04 monolevel 0.000000000 12 37063001588101 2022-01-04 monolevel 0.000000000 13 37183001488101 2022-01-05 monolevel 0.003906250 14 37183002188101 2022-01-05 monolevel 0.001953125 15 37063001588101 2022-01-05 monolevel 0.001953125"},{"path":[]},{"path":"https://kyle-messier.github.io/amadeus/reference/as_mysftime.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert to sftime object on the form adapted to beethoven code — as_mysftime","title":"Convert to sftime object on the form adapted to beethoven code — as_mysftime","text":"Convert sftime object form adapted beethoven code","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/as_mysftime.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert to sftime object on the form adapted to beethoven code — as_mysftime","text":"","code":"as_mysftime(x, ...)"},{"path":"https://kyle-messier.github.io/amadeus/reference/as_mysftime.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert to sftime object on the form adapted to beethoven code — as_mysftime","text":"x data.frame, data.table, SpatVector SpatRasterDataset ... x data.frame data.table: lonname, latname, timename crs arguments required. x sf sftime, timename argument required. x terra::SpatRaster, varname argument required.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/as_mysftime.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert to sftime object on the form adapted to beethoven code — as_mysftime","text":"sftime object constrained time column name (see check_mysftime() function)","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/as_mysftime.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Convert to sftime object on the form adapted to beethoven code — as_mysftime","text":"Eva Marques","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_covariates.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate covariates — calc_covariates","title":"Calculate covariates — calc_covariates","text":"Calculate covariates","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_covariates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate covariates — calc_covariates","text":"","code":"calc_covariates( covariate = c(\"modis\", \"koppen-geiger\", \"koeppen-geiger\", \"koppen\", \"koeppen\", \"geos\", \"dummies\", \"gmted\", \"roads\", \"ecoregions\", \"ecoregion\", \"hms\", \"noaa\", \"smoke\", \"gmted\", \"narr\", \"narr_monolevel\", \"narr_p_levels\", \"plevels\", \"monolevel\", \"p_levels\", \"geos\", \"sedac_population\", \"population\"), locs, from, locs_id = \"site_id\", ... )"},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_covariates.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate covariates — calc_covariates","text":"covariate character(1). Covariate type. locs sf/SpatVector. Unique locations. include unique identifier field named locs_id character. Single multiple strings. locs_id character(1). Name unique identifier. Default \"site_id\". ... Arguments passed covariate calculation function.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_covariates.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate covariates — calc_covariates","text":"Calculated covariates. Mainly data.frame object.","code":""},{"path":[]},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_covariates.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate covariates — calc_covariates","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_ecoregion.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate EPA Ecoregions level 2/3 binary variables — calc_ecoregion","title":"Calculate EPA Ecoregions level 2/3 binary variables — calc_ecoregion","text":"Calculate EPA Ecoregions level 2/3 binary variables","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_ecoregion.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate EPA Ecoregions level 2/3 binary variables — calc_ecoregion","text":"","code":"calc_ecoregion(locs, from = NULL, locs_id = \"site_id\", ...)"},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_ecoregion.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate EPA Ecoregions level 2/3 binary variables — calc_ecoregion","text":"locs sf/SpatVector. Unique locs. include unique identifier field named locs_id SpatVector. Ecoregion polygons locs_id character(1). Name unique identifier. ... Placeholders.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_ecoregion.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate EPA Ecoregions level 2/3 binary variables — calc_ecoregion","text":"data.frame object dummy variables attributes : attr(., \"ecoregion2_code\"): Ecoregion lv.2 code key attr(., \"ecoregion3_code\"): Ecoregion lv.3 code key","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_ecoregion.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate EPA Ecoregions level 2/3 binary variables — calc_ecoregion","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_geos.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate NASA GEOS-CF meteorological and atmospheric covariates — calc_geos","title":"Calculate NASA GEOS-CF meteorological and atmospheric covariates — calc_geos","text":"Extract GEOS-CF data point locations using SpatRaster object process_geos. Function returns data frame containing GEOS-CF variable values user-defined sites. Unique column names reflect variable name, circular buffer, vertical pressure level (applicable).","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_geos.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate NASA GEOS-CF meteorological and atmospheric covariates — calc_geos","text":"","code":"calc_geos(from, locs, locs_id = NULL, radius = 0, fun = \"mean\")"},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_geos.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate NASA GEOS-CF meteorological and atmospheric covariates — calc_geos","text":"SpatRaster(1). Cleaned SpatRaster object returned process_eos containing GEOS-CF variable data. locs data.frame, characater file path, SpatVector, sf object. locs_id character(1). Column within locations CSV file containing identifier unique coordinate location. radius integer(1). Circular buffer distance around site locations. (Default = 0). fun character(1). Function used summarize multiple raster cells within sites location buffer (Default = mean).","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_geos.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate NASA GEOS-CF meteorological and atmospheric covariates — calc_geos","text":"data.frame object;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_geos.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate NASA GEOS-CF meteorological and atmospheric covariates — calc_geos","text":"Mitchell Manware","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_gmted.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate GMTED elevation covariates — calc_gmted","title":"Calculate GMTED elevation covariates — calc_gmted","text":"Extract Global Multi-resolution Terrain Elevation Data (GMTED2010) data point locations using SpatRaster object process_gmted. Function returns data frame containing GMTED variable values user-defined sites. Unique column reflect statistic, resolution, circular buffer.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_gmted.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate GMTED elevation covariates — calc_gmted","text":"","code":"calc_gmted(from, locs, locs_id = NULL, radius = 0, fun = \"mean\")"},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_gmted.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate GMTED elevation covariates — calc_gmted","text":"SpatRaster(1). Cleaned SpatRaster object returned process_gmted containing Global Multi-resolution Terrain Elevation Data (GMTED2010) data. locs data.frame. character file path, SpatVector, sf object. locs_id character(1). Column within locations CSV file containing identifier unique coordinate location. radius integer(1). Circular buffer distance around site locations. (Default = 0). fun character(1). Function used summarize multiple raster cells within sites location buffer (Default = mean).","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_gmted.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate GMTED elevation covariates — calc_gmted","text":"data.frame object;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_gmted.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate GMTED elevation covariates — calc_gmted","text":"Mitchell Manware","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_hms.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate NOAA HMS Wildfire Smoke covariates — calc_hms","title":"Calculate NOAA HMS Wildfire Smoke covariates — calc_hms","text":"Extract wildfire smoke plume coverage data NOAA Hazard Mapping Fire Smoke Product point locations using SpatVector object process_hms. Function returns data frame containing wildfire smoke plume binary values (0 = smoke absent; 1 = smoke present) user-defined sites. Unique columns reflect smoke density circular buffer.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_hms.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate NOAA HMS Wildfire Smoke covariates — calc_hms","text":"","code":"calc_hms(from, locs, locs_id = NULL, radius = 0)"},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_hms.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate NOAA HMS Wildfire Smoke covariates — calc_hms","text":"SpatVector(1). Cleaned SpatVector object returned process_hms containing wildfire smoke plume coverage data. locs data.frame, characater file path, SpatVector, sf object. locs_id character(1). Column within locations CSV file containing identifier unique coordinate location. radius integer(1). Circular buffer distance around site locations. (Default = 0).","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_hms.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate NOAA HMS Wildfire Smoke covariates — calc_hms","text":"data.frame object;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_hms.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate NOAA HMS Wildfire Smoke covariates — calc_hms","text":"Mitchell Manware","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_koppen_geiger.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate Koeppen-Geiger climate zone binary variables — calc_koppen_geiger","title":"Calculate Koeppen-Geiger climate zone binary variables — calc_koppen_geiger","text":"Calculate Koeppen-Geiger climate zone binary variables","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_koppen_geiger.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate Koeppen-Geiger climate zone binary variables — calc_koppen_geiger","text":"","code":"calc_koppen_geiger(locs = NULL, from = NULL, locs_id = \"site_id\", ...)"},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_koppen_geiger.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate Koeppen-Geiger climate zone binary variables — calc_koppen_geiger","text":"locs sf/SpatVector. Unique locs. include unique identifier field named locs_id character(1). Koppen-Geiger climate zone raster file locs_id character(1). Name unique identifier. ... Placeholders.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_koppen_geiger.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate Koeppen-Geiger climate zone binary variables — calc_koppen_geiger","text":"data.frame object","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_koppen_geiger.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate Koeppen-Geiger climate zone binary variables — calc_koppen_geiger","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_modis_daily.html","id":null,"dir":"Reference","previous_headings":"","what":"A single-date MODIS worker for parallelization — calc_modis_daily","title":"A single-date MODIS worker for parallelization — calc_modis_daily","text":"modis_worker operates six MODIS/VIIRS products (MOD11A1, MOD13A2, MOD06_L2, VNP46A2, MOD09GA, MCD19A2) daily basis. Given raw hdf files downloaded NASA, standard file names include data retrieval date flag starting . Leveraging piece information, function select files scope date interest. Please note function provide function filter swaths tiles, strongly recommended check pre-filter file names users' discretion.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_modis_daily.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"A single-date MODIS worker for parallelization — calc_modis_daily","text":"","code":"calc_modis_daily( locs = NULL, from = NULL, locs_id = \"site_id\", date = NULL, name_extracted = NULL, fun_summary = \"mean\", radius = 0L, ... )"},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_modis_daily.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"A single-date MODIS worker for parallelization — calc_modis_daily","text":"locs SpatVector/sf/sftime object. Locations MODIS values summarized. SpatRaster. Preprocessed objects. locs_id character(1). Field name unique site identifiers stored. Default \"site_id\" date Date(1). date query. name_extracted character. Names calculated covariates. fun_summary function. Summary function multilayer rasters. Passed foo. See exactextractr::exact_extract details. radius numeric. Radius generate circular buffers. ... Placeholders.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_modis_daily.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"A single-date MODIS worker for parallelization — calc_modis_daily","text":"data.frame object.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_modis_daily.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"A single-date MODIS worker for parallelization — calc_modis_daily","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_modis_par.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate MODIS product covariates in multiple CPU threads — calc_modis_par","title":"Calculate MODIS product covariates in multiple CPU threads — calc_modis_par","text":"calc_modis_par essentially runs calc_modis_daily function thread (subprocess). Based daily resolution, day's workload distributed thread. product argument, files processed customized function unique structure /characteristics products considered. nthreads argument carefully selected consideration machine's CPU memory capacities products memory pressure. locs sf object exportable parallel workers.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_modis_par.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate MODIS product covariates in multiple CPU threads — calc_modis_par","text":"","code":"calc_modis_par( locs = NULL, from = NULL, locs_id = \"site_id\", preprocess = process_modis_merge, name_covariates = NULL, radius = c(0L, 1000L, 10000L, 50000L), subdataset = NULL, fun_summary = \"mean\", nthreads = floor(length(parallelly::availableWorkers())/2), package_list_add = NULL, export_list_add = NULL, ... )"},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_modis_par.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate MODIS product covariates in multiple CPU threads — calc_modis_par","text":"locs sf/SpatVector object. Unique locs covariates calculated. character. List paths MODIS/VIIRS files. locs_id character(1). Site identifier. Default \"site_id\" preprocess function. Function handle HDF files. name_covariates character. Name header covariates. e.g., \"MOD_NDVIF_0_\". calculated covariate names form 'name_covariateszero-padded buffer radius meters', e.g., 'MOD_NDVIF_0_50000' 50 km radius circular buffer used calculate mean NDVI value. radius numeric. Radii calculate covariates. Default c(0, 1000, 10000, 50000). subdataset Index search pattern subdataset. fun_summary character function. Function summarize extracted raster values. nthreads integer(1). Number threads used calculate covariates. package_list_add character. vector package names load thread. Note sf, terra, exactextractr, doParallel, parallelly dplyr default packages loaded. export_list_add character. vector object names export thread. minimized spare memory. ... Arguments passed preprocess.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_modis_par.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate MODIS product covariates in multiple CPU threads — calc_modis_par","text":"Overall, function dependent routines assume file system can handle concurrent access (network) disk multiple processes. File system characteristics, package versions, hardware settings specification can affect processing efficiency. locs expected convertible sf object. sf, SpatVector, class objects converted sf can used. Common arguments preprocess functions date path automatically detected passed function. Please note locs path preprocess functions assumed standard naming convention raw files NASA.","code":""},{"path":[]},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_narr.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate NOAA NCEP North American Regional Reanalysis meteorological\nand atmospheric covariates — calc_narr","title":"Calculate NOAA NCEP North American Regional Reanalysis meteorological\nand atmospheric covariates — calc_narr","text":"Extract NOAA NCEP North American Regional Reanalysis (NARR) data point locations using SpatRaster object process_narr. Function returns data frame containing NARR variable values user-defined sites. Unique column names reflect variable name, circular buffer, vertical pressure level (applicable).","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_narr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate NOAA NCEP North American Regional Reanalysis meteorological\nand atmospheric covariates — calc_narr","text":"","code":"calc_narr(from, locs, locs_id = NULL, radius = 0, fun = \"mean\")"},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_narr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate NOAA NCEP North American Regional Reanalysis meteorological\nand atmospheric covariates — calc_narr","text":"SpatRaster(1). Cleaned SpatRaster object returned process_narr containing NOAA NCEP North American Regional Reanalysis variable data. locs data.frame, characater file path, SpatVector, sf object. locs_id character(1). Column within locations CSV file containing identifier unique coordinate location. radius integer(1). Circular buffer distance around site locations. (Default = 0). fun character(1). Function used summarize multiple raster cells within sites location buffer (Default = mean).","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_narr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate NOAA NCEP North American Regional Reanalysis meteorological\nand atmospheric covariates — calc_narr","text":"data.frame object;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_narr.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate NOAA NCEP North American Regional Reanalysis meteorological\nand atmospheric covariates — calc_narr","text":"Mitchell Manware","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_nei.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate National Emission Inventory (NEI) covariates — calc_nei","title":"Calculate National Emission Inventory (NEI) covariates — calc_nei","text":"Calculate National Emission Inventory (NEI) covariates","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_nei.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate National Emission Inventory (NEI) covariates — calc_nei","text":"","code":"calc_nei(locs = NULL, from = NULL, locs_id = \"site_id\", ...)"},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_nei.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate National Emission Inventory (NEI) covariates — calc_nei","text":"locs sf/SpatVector. Locations NEI values joined. character(1). directory NEI CSV files locs_id character(1). Unique site identifier column name. Unused kept compatibility. ... Placeholders.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_nei.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate National Emission Inventory (NEI) covariates — calc_nei","text":"data.frame object.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_nei.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate National Emission Inventory (NEI) covariates — calc_nei","text":"Insang Song, Ranadeep Daw","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_nlcd_ratio.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute land cover classes ratio in circle buffers around points — calc_nlcd_ratio","title":"Compute land cover classes ratio in circle buffers around points — calc_nlcd_ratio","text":"Compute land cover classes ratio circle buffers around points","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_nlcd_ratio.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute land cover classes ratio in circle buffers around points — calc_nlcd_ratio","text":"","code":"calc_nlcd_ratio(locs, from, locs_id = \"site_id\", radius = 1000, ...)"},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_nlcd_ratio.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute land cover classes ratio in circle buffers around points — calc_nlcd_ratio","text":"locs terra::SpatVector points geometry SpatRaster NLCD locs_id character(1). Unique identifier locations radius numeric (non-negative) giving radius buffer around points ... Placeholders.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedac_groads.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate SEDAC groads density covariates — calc_sedac_groads","title":"Calculate SEDAC groads density covariates — calc_sedac_groads","text":"Prepared groads data clipped buffer polygons radius. total length roads calculated. density roads calculated dividing total length area buffer. terra::linearUnits() used convert unit length meters.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedac_groads.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate SEDAC groads density covariates — calc_sedac_groads","text":"","code":"calc_sedac_groads( from = NULL, locs = NULL, locs_id = NULL, radius = 1000, fun = sum )"},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedac_groads.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate SEDAC groads density covariates — calc_sedac_groads","text":"SpatVector(1). Output process_sedac_groads. locs data.frame, characater file path, SpatVector, sf object. locs_id character(1). Column within locations CSV file containing identifier unique coordinate location. radius integer(1). Circular buffer distance around site locations. (Default = 1000). fun function(1). Function used summarize length roads within sites location buffer (Default sum).","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedac_groads.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate SEDAC groads density covariates — calc_sedac_groads","text":"data.frame object three columns.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedac_groads.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate SEDAC groads density covariates — calc_sedac_groads","text":"Unit km / sq km.","code":""},{"path":[]},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedac_groads.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate SEDAC groads density covariates — calc_sedac_groads","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedac_population.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate UN WPP-Ajusted population density covariates — calc_sedac_population","title":"Calculate UN WPP-Ajusted population density covariates — calc_sedac_population","text":"Extract population density data point locations using SpatRaster object process_sedac_population. Function returns data frame containing population values user-defined sites. Unique column names reflect variable name circular buffer.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedac_population.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate UN WPP-Ajusted population density covariates — calc_sedac_population","text":"","code":"calc_sedac_population(from, locs, locs_id = NULL, radius = 0, fun = \"mean\")"},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedac_population.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate UN WPP-Ajusted population density covariates — calc_sedac_population","text":"SpatRaster(1). Cleaned SpatRaster object returned process_sedac_population containing GEOS-CF variable data. locs data.frame, characater file path, SpatVector, sf object. locs_id character(1). Column within locations CSV file containing identifier unique coordinate location. radius integer(1). Circular buffer distance around site locations. (Default = 0). fun character(1). Function used summarize multiple raster cells within sites location buffer (Default = mean).","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedac_population.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate UN WPP-Ajusted population density covariates — calc_sedac_population","text":"data.frame object;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedac_population.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate UN WPP-Ajusted population density covariates — calc_sedac_population","text":"Mitchell Manware","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedc.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate Sum of Exponentially Decaying Contributions (SEDC) covariates — calc_sedc","title":"Calculate Sum of Exponentially Decaying Contributions (SEDC) covariates — calc_sedc","text":"Calculate Sum Exponentially Decaying Contributions (SEDC) covariates","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedc.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate Sum of Exponentially Decaying Contributions (SEDC) covariates — calc_sedc","text":"","code":"calc_sedc( locs = NULL, from = NULL, locs_id = NULL, sedc_bandwidth = NULL, target_fields = NULL )"},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedc.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate Sum of Exponentially Decaying Contributions (SEDC) covariates — calc_sedc","text":"locs SpatVector object. Locations sum SEDCs calculated. SpatVector object. Locations SEDC calculated. locs_id character(1). Name unique id field point_to. sedc_bandwidth numeric(1). Distance source concentration reduced exp(-3) (approximately -95 %) target_fields character(varying). Field names characters.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedc.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate Sum of Exponentially Decaying Contributions (SEDC) covariates — calc_sedc","text":"data.frame (tibble) object input field names suffix \"_sedc\" sums EDC stored. Additional attributes attached EDC information. `attr(result, \"sedc_bandwidth\")``: bandwidth concentration reduces approximately five percent `attr(result, \"sedc_threshold\")``: threshold distance emission source points excluded beyond ","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedc.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate Sum of Exponentially Decaying Contributions (SEDC) covariates — calc_sedc","text":"function originally chopin Distance calculation done terra functions internally. Thus, function internally converts sf objects point_* arguments terra. threshold carefully chosen users.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedc.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculate Sum of Exponentially Decaying Contributions (SEDC) covariates — calc_sedc","text":"Messier KP, Akita Y, & Serre ML. (2012). Integrating Address Geocoding, Land Use Regression, Spatiotemporal Geostatistical Estimation Groundwater Tetrachloroethylene. Environmental Science & Technology 46(5), 2772-2780. Wiesner C. (n.d.). Euclidean Sum Exponentially Decaying Contributions Tutorial","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedc.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate Sum of Exponentially Decaying Contributions (SEDC) covariates — calc_sedc","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_sedc.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate Sum of Exponentially Decaying Contributions (SEDC) covariates — calc_sedc","text":"","code":"library(terra) #> terra 1.7.71 library(sf) #> Linking to GEOS 3.10.2, GDAL 3.4.1, PROJ 8.2.1; sf_use_s2() is TRUE set.seed(101) ncpath <- system.file(\"gpkg/nc.gpkg\", package = \"sf\") nc <- terra::vect(ncpath) nc <- terra::project(nc, \"EPSG:5070\") pnt_locs <- terra::centroids(nc, inside = TRUE) pnt_locs <- pnt_locs[, \"NAME\"] pnt_from <- terra::spatSample(nc, 100L) pnt_from$pid <- seq(1, 100) pnt_from <- pnt_from[, \"pid\"] pnt_from$val1 <- rgamma(100L, 1, 0.05) pnt_from$val2 <- rgamma(100L, 2, 1) vals <- c(\"val1\", \"val2\") calc_sedc(pnt_locs, pnt_from, \"NAME\", 1e5, vals) #> Joining with `by = join_by(from_id)` #> Joining with `by = join_by(to_id)` #> Joining with `by = join_by(from_id, to_id)` #> # A tibble: 100 × 3 #> NAME val1 val2 #> #> 1 Alamance 66.3 6.71 #> 2 Alexander 98.0 11.7 #> 3 Alleghany 135. 8.57 #> 4 Anson 50.0 5.23 #> 5 Ashe 143. 8.42 #> 6 Avery 76.1 8.76 #> 7 Beaufort 58.8 6.29 #> 8 Bertie 70.1 7.85 #> 9 Bladen 79.5 6.82 #> 10 Brunswick 54.3 5.34 #> # ℹ 90 more rows"},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_temporal_dummies.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate temporal dummy variables — calc_temporal_dummies","title":"Calculate temporal dummy variables — calc_temporal_dummies","text":"Calculate temporal dummy variables","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_temporal_dummies.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate temporal dummy variables — calc_temporal_dummies","text":"","code":"calc_temporal_dummies( locs, from = NULL, locs_id = \"site_id\", year = seq(2018L, 2022L), ... )"},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_temporal_dummies.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate temporal dummy variables — calc_temporal_dummies","text":"locs data.frame temporal field named \"time\" used. locs_id character(1). Unique site identifier column name. Default \"site_id\". year integer. Year domain dummify. Default seq(2018L, 2022L) ... Placeholders.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_temporal_dummies.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate temporal dummy variables — calc_temporal_dummies","text":"data.frame year, month, weekday indicators.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_temporal_dummies.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate temporal dummy variables — calc_temporal_dummies","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_tri.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate TRI covariates — calc_tri","title":"Calculate TRI covariates — calc_tri","text":"Calculate TRI covariates","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_tri.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate TRI covariates — calc_tri","text":"","code":"calc_tri( locs, from = NULL, locs_id = \"site_id\", radius = c(1000L, 10000L, 50000L), ... )"},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_tri.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate TRI covariates — calc_tri","text":"locs sf/SpatVector. Locations TRI variables calculated. SpatVector. Point vector object TRI year. See process_tri locs_id character(1). Unique site identifier column name. Default \"site_id\". radius Circular buffer radius. Default c(1000, 10000, 50000) (meters) ... Placeholders.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_tri.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate TRI covariates — calc_tri","text":"data.frame object.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_tri.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate TRI covariates — calc_tri","text":"U.S. context.","code":""},{"path":[]},{"path":"https://kyle-messier.github.io/amadeus/reference/calc_tri.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate TRI covariates — calc_tri","text":"Insang Song, Mariana Kassien","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/check_for_null_parameters.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for null arguments — check_for_null_parameters","title":"Check for null arguments — check_for_null_parameters","text":"Check null arguments","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/check_for_null_parameters.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for null arguments — check_for_null_parameters","text":"","code":"check_for_null_parameters(parameters)"},{"path":"https://kyle-messier.github.io/amadeus/reference/check_for_null_parameters.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for null arguments — check_for_null_parameters","text":"parameters parameters passed function (called mget(ls()).)","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/check_mysf.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if the sf object is formated on a specific way — check_mysf","title":"Check if the sf object is formated on a specific way — check_mysf","text":"Check sf object formated specific way","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/check_mysf.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if the sf object is formated on a specific way — check_mysf","text":"","code":"check_mysf(x)"},{"path":"https://kyle-messier.github.io/amadeus/reference/check_mysf.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if the sf object is formated on a specific way — check_mysf","text":"x sf object","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/check_mysf.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Check if the sf object is formated on a specific way — check_mysf","text":"Eva Marques","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/check_mysftime.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if the sftime object is formated on a specific way — check_mysftime","title":"Check if the sftime object is formated on a specific way — check_mysftime","text":"Check sftime object formated specific way","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/check_mysftime.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if the sftime object is formated on a specific way — check_mysftime","text":"","code":"check_mysftime(x)"},{"path":"https://kyle-messier.github.io/amadeus/reference/check_mysftime.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if the sftime object is formated on a specific way — check_mysftime","text":"x sftime object","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/check_mysftime.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Check if the sftime object is formated on a specific way — check_mysftime","text":"Eva Marques","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/check_url_status.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if sample of download URLs have HTTP Status 200 — check_url_status","title":"Check if sample of download URLs have HTTP Status 200 — check_url_status","text":"Check sample download URLs HTTP Status 200","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/check_url_status.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if sample of download URLs have HTTP Status 200 — check_url_status","text":"","code":"check_url_status(url, method = c(\"HEAD\", \"GET\"))"},{"path":"https://kyle-messier.github.io/amadeus/reference/check_url_status.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if sample of download URLs have HTTP Status 200 — check_url_status","text":"url Download URL checked. method httr method obtain URL (\"HEAD\" \"GET\")","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/check_url_status.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if sample of download URLs have HTTP Status 200 — check_url_status","text":"logical object","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/check_url_status.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Check if sample of download URLs have HTTP Status 200 — check_url_status","text":"Insang Song; Mitchell Manware","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/check_urls.html","id":null,"dir":"Reference","previous_headings":"","what":"Sample download URLs and apply check_url_status function — check_urls","title":"Sample download URLs and apply check_url_status function — check_urls","text":"Sample download URLs apply check_url_status function","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/check_urls.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Sample download URLs and apply check_url_status function — check_urls","text":"","code":"check_urls(urls = urls, size = NULL, method = c(\"HEAD\", \"GET\", \"SKIP\"))"},{"path":"https://kyle-messier.github.io/amadeus/reference/check_urls.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Sample download URLs and apply check_url_status function — check_urls","text":"urls character vector URLs size number observations sampled urls method httr method obtain URL (\"HEAD\" \"GET\"). set \"SKIP\", HTTP status checked returned.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/check_urls.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Sample download URLs and apply check_url_status function — check_urls","text":"logical vector URL status = 200","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_aqs_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download daily data from AQS datamart — download_aqs_data","title":"Download daily data from AQS datamart — download_aqs_data","text":"Download daily data AQS datamart","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_aqs_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download daily data from AQS datamart — download_aqs_data","text":"","code":"download_aqs_data( parameter_code = 88101, year_start = 2018, year_end = 2022, resolution_temporal = \"daily\", directory_to_download = NULL, directory_to_save = NULL, url_aqs_download = \"https://aqs.epa.gov/aqsweb/airdata/\", data_download_acknowledgement = FALSE, unzip = TRUE, remove_zip = FALSE, download = FALSE, remove_command = FALSE )"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_aqs_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download daily data from AQS datamart — download_aqs_data","text":"parameter_code integer(1). length 5. EPA pollutant parameter code. details, please refer AQS parameter codes year_start integer(1). length 4. Start year downloading data. year_end integer(1). length 4. End year downloading data. resolution_temporal character(1). Name column containing POC values. Currently, value \"daily\" works. directory_to_download character(1). Directory download zip files AQS data mart. directory_to_save character(1). Directory decompress zip files. url_aqs_download character(1). URL AQS pre-generated datasets. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. unzip logical(1). Unzip zip files. Default TRUE. remove_zip logical(1). Remove zip file directory_to_download. Default FALSE. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands. Default FALSE.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_aqs_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download daily data from AQS datamart — download_aqs_data","text":"NULL; Separate comma-separated value (CSV) files monitors daily representative values stored directory_to_save.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_aqs_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download daily data from AQS datamart — download_aqs_data","text":"Mariana Kassien, Insang Song, Mitchell Manware","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download raw data from sources — download_data","title":"Download raw data from sources — download_data","text":"Download raw data sources","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download raw data from sources — download_data","text":"","code":"download_data( dataset_name = c(\"aqs\", \"ecoregion\", \"geos\", \"gmted\", \"koppen\", \"koppengeiger\", \"merra2\", \"merra\", \"narr_monolevel\", \"modis\", \"narr_p_levels\", \"nlcd\", \"noaa\", \"sedac_groads\", \"sedac_population\", \"groads\", \"population\", \"plevels\", \"p_levels\", \"monolevel\", \"hms\", \"smoke\", \"tri\", \"nei\"), directory_to_save = NULL, data_download_acknowledgement = FALSE, ... )"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download raw data from sources — download_data","text":"dataset_name character(1). Dataset download. directory_to_save character(1). Directory save / unzip (zip files downloaded) data. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. ... Arguments passed download function.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_data.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Download raw data from sources — download_data","text":"download function names download_*_data formats","code":""},{"path":[]},{"path":"https://kyle-messier.github.io/amadeus/reference/download_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download raw data from sources — download_data","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_ecoregion_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download Ecoregion Shapefiles from EPA — download_ecoregion_data","title":"Download Ecoregion Shapefiles from EPA — download_ecoregion_data","text":"download_ecoregion_data() function accesses downloads Ecoregions level 3 data, pieces information higher levels included.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_ecoregion_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download Ecoregion Shapefiles from EPA — download_ecoregion_data","text":"","code":"download_ecoregion_data( directory_to_download = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, unzip = TRUE, remove_zip = FALSE, download = FALSE, remove_command = TRUE, epa_certificate_path = system.file(\"extdata/cacert_gaftp_epa.pem\", package = \"amadeus\"), certificate_url = \"http://cacerts.digicert.com/DigiCertGlobalG2TLSRSASHA2562020CA1-1.crt\" )"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_ecoregion_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download Ecoregion Shapefiles from EPA — download_ecoregion_data","text":"directory_to_download character(1). Directory download zip file Ecoregion level 3 shapefiles directory_to_save character(1). Directory decompress zip files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. unzip logical(1). Unzip zip files. Default TRUE. remove_zip logical(1). Remove zip file directory_to_download. Default FALSE. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands. epa_certificate_path character(1). Path certificate file EPA DataCommons. Default 'extdata/cacert_gaftp_epa.pem' package installation path. certificate_url character(1). URL certificate file. See notes details.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_ecoregion_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download Ecoregion Shapefiles from EPA — download_ecoregion_data","text":"NULL;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_ecoregion_data.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Download Ecoregion Shapefiles from EPA — download_ecoregion_data","text":"EPA Data Commons certificate errors, follow steps : Click Lock icon address bar https://gaftp.epa.gov Click Show Certificate Access Details Find URL *.crt extension Currently bundle pre-downloaded crt PEM (accepted wget command) file ./inst/extdata. instruction certificate updates future.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_ecoregion_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download Ecoregion Shapefiles from EPA — download_ecoregion_data","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_epa_certificate.html","id":null,"dir":"Reference","previous_headings":"","what":"Check EPA Certificate — download_epa_certificate","title":"Check EPA Certificate — download_epa_certificate","text":"Check EPA Certificate","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_epa_certificate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check EPA Certificate — download_epa_certificate","text":"","code":"download_epa_certificate( epa_certificate_path = \"cacert_gaftp_epa.pem\", certificate_url = \"http://cacerts.digicert.com/DigiCertGlobalG2TLSRSASHA2562020CA1-1.crt\" )"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_epa_certificate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check EPA Certificate — download_epa_certificate","text":"epa_certificate_path character(1). Full path converted certificate EPA. end .pem certificate_url character(1). URL original certificate.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_epa_certificate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check EPA Certificate — download_epa_certificate","text":"file designated epa_certificate_path","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_epa_certificate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Check EPA Certificate — download_epa_certificate","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_geos_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download atmospheric composition data from the NASA Global Earth Observing System (GEOS) model. — download_geos_data","title":"Download atmospheric composition data from the NASA Global Earth Observing System (GEOS) model. — download_geos_data","text":"download_geos_data() function accesses downloads various atmospheric composition collections NASA Global Earth Observing System (GEOS) model.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_geos_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download atmospheric composition data from the NASA Global Earth Observing System (GEOS) model. — download_geos_data","text":"","code":"download_geos_data( date_start = \"2023-09-01\", date_end = \"2023-09-01\", collection = c(\"aqc_tavg_1hr_g1440x721_v1\", \"chm_tavg_1hr_g1440x721_v1\", \"met_tavg_1hr_g1440x721_x1\", \"xgc_tavg_1hr_g1440x721_x1\", \"chm_inst_1hr_g1440x721_p23\", \"met_inst_1hr_g1440x721_p23\"), directory_to_save = NULL, data_download_acknowledgement = FALSE, download = FALSE, remove_command = FALSE )"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_geos_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download atmospheric composition data from the NASA Global Earth Observing System (GEOS) model. — download_geos_data","text":"date_start character(1). length 10. Start date downloading data. Format YYYY-MM-DD (ex. September 1, 2023 = \"2023-09-01\"). date_end character(1). length 10. End date downloading data. Format YYYY-MM-DD (ex. September 1, 2023 = \"2023-09-01\"). collection character(1). GEOS-CF data collection file name. directory_to_save character(1). Directory save data. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_geos_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download atmospheric composition data from the NASA Global Earth Observing System (GEOS) model. — download_geos_data","text":"NULL;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_geos_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download atmospheric composition data from the NASA Global Earth Observing System (GEOS) model. — download_geos_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_gmted_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download global elevation data from the Global Multi-resolution Terrain Elevation Data (GMTED2010). — download_gmted_data","title":"Download global elevation data from the Global Multi-resolution Terrain Elevation Data (GMTED2010). — download_gmted_data","text":"download_gmted_data() function acesses downloads Global Multi-resolution Terrain Elevation Data (GMTED2010) U.S. Geological Survey National Geospatial-Intelligence Agency.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_gmted_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download global elevation data from the Global Multi-resolution Terrain Elevation Data (GMTED2010). — download_gmted_data","text":"","code":"download_gmted_data( statistic = c(\"Breakline Emphasis\", \"Systematic Subsample\", \"Median Statistic\", \"Minimum Statistic\", \"Mean Statistic\", \"Maximum Statistic\", \"Standard Deviation Statistic\"), resolution = c(\"7.5 arc-seconds\", \"15 arc-seconds\", \"30 arc-seconds\"), directory_to_download = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, unzip = TRUE, remove_zip = FALSE, download = FALSE, remove_command = FALSE )"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_gmted_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download global elevation data from the Global Multi-resolution Terrain Elevation Data (GMTED2010). — download_gmted_data","text":"statistic character(1). Available statistics include \"Breakline Emphasis\", \"Systematic Subsample\", \"Median Statistic\", \"Minimum Statistic\", \"Mean Statistic\", \"Maximum Statistic\", \"Standard Deviation Statistic\". resolution character(1). Available resolutions include \"7.5 arc-seconds\", \"15 arc-seconds\", \"30 arc-seconds\". directory_to_download character(1). Directory download zip files Global Multi-resolution Terrain Elevation Data (GMTED2010). directory_to_save character(1). Directory decompress zip files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. unzip logical(1). Unzip zip files. Default TRUE. remove_zip logical(1). Remove zip file directory_to_download. Default FALSE. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands. Default FALSE.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_gmted_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download global elevation data from the Global Multi-resolution Terrain Elevation Data (GMTED2010). — download_gmted_data","text":"NULL;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_gmted_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download global elevation data from the Global Multi-resolution Terrain Elevation Data (GMTED2010). — download_gmted_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_hms_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download daily wildfire smoke plume data from NOAA Hazard Mapping System Fire and Smoke Product — download_hms_data","title":"Download daily wildfire smoke plume data from NOAA Hazard Mapping System Fire and Smoke Product — download_hms_data","text":"download_hms_data() function accesses downloads wildfire smoke plume coverage data National Oceanic Atmospheric Administration's (NOAA) Hazard Mapping System Fire Smoke Product.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_hms_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download daily wildfire smoke plume data from NOAA Hazard Mapping System Fire and Smoke Product — download_hms_data","text":"","code":"download_hms_data( date_start = \"2023-09-01\", date_end = \"2023-09-01\", data_format = \"Shapefile\", directory_to_download = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, download = FALSE, remove_command = FALSE, unzip = TRUE, remove_zip = FALSE )"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_hms_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download daily wildfire smoke plume data from NOAA Hazard Mapping System Fire and Smoke Product — download_hms_data","text":"date_start character(1). length 10. Start date downloading data. Format YYYY-MM-DD (ex. September 1, 2023 \"2023-09-01\"). date_end character(1). length 10. End date downloading data. Format YYYY-MM-DD (ex. September 10, 2023 \"2023-09-10\"). data_format character(1). \"Shapefile\" \"KML\". directory_to_download character(1). Directory download zip files NOAA Hazard Mapping System Fire Smoke Product. (Ignored data_format = \"KML\".) directory_to_save character(1). Directory save unzipped shapefiles KML files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands. unzip logical(1). Unzip zip files. Default TRUE. (Ignored data_format = \"KML\".) remove_zip logical(1). Remove zip files directory_to_download. Default FALSE. (Ignored data_format = \"KML\".)","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_hms_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download daily wildfire smoke plume data from NOAA Hazard Mapping System Fire and Smoke Product — download_hms_data","text":"NULL;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_hms_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download daily wildfire smoke plume data from NOAA Hazard Mapping System Fire and Smoke Product — download_hms_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_koppen_geiger_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download climate classification data from the present and future Köppen-Geiger climate classification maps. — download_koppen_geiger_data","title":"Download climate classification data from the present and future Köppen-Geiger climate classification maps. — download_koppen_geiger_data","text":"download_koppen_geiger_data() function accesses downloads climate classification data Present future Köppen-Geiger climate classification maps 1-km resolution (link article; link data).","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_koppen_geiger_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download climate classification data from the present and future Köppen-Geiger climate classification maps. — download_koppen_geiger_data","text":"","code":"download_koppen_geiger_data( time_period = c(\"Present\", \"Future\"), data_resolution = c(\"0.0083\", \"0.083\", \"0.5\"), directory_to_download = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, download = FALSE, unzip = TRUE, remove_zip = FALSE, remove_command = FALSE )"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_koppen_geiger_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download climate classification data from the present and future Köppen-Geiger climate classification maps. — download_koppen_geiger_data","text":"time_period character(1). Available times \"Present\" (1980-2016) \"Future\" (2071-2100). (\"Future\" classifications based scenario RCP8.5). data_resolution character(1). Available resolutions \"0.0083\" degrees (approx. 1 km), \"0.083\" degrees (approx. 10 km), \"0.5\" degrees (approx. 50 km). directory_to_download character(1). Directory download zip files Present future Köppen-Geiger climate classification maps 1-km resolution. directory_to_save character(1). Directory decompress zip files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. unzip logical(1). Unzip zip files. Default TRUE. remove_zip logical(1). Remove zip files directory_to_download. Default FALSE. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_koppen_geiger_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download climate classification data from the present and future Köppen-Geiger climate classification maps. — download_koppen_geiger_data","text":"NULL;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_koppen_geiger_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download climate classification data from the present and future Köppen-Geiger climate classification maps. — download_koppen_geiger_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_merra2_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download meteorological and atmospheric data from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) model. — download_merra2_data","title":"Download meteorological and atmospheric data from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) model. — download_merra2_data","text":"download_merra2_data() function accesses downloads various meteorological atmospheric collections Modern-Era Retrospective analysis Research Applications, Version 2 (MERRA-2).","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_merra2_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download meteorological and atmospheric data from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) model. — download_merra2_data","text":"","code":"download_merra2_data( date_start = \"2023-09-01\", date_end = \"2023-09-01\", collection = c(\"inst1_2d_asm_Nx\", \"inst1_2d_int_Nx\", \"inst1_2d_lfo_Nx\", \"inst3_3d_asm_Np\", \"inst3_3d_aer_Nv\", \"inst3_3d_asm_Nv\", \"inst3_3d_chm_Nv\", \"inst3_3d_gas_Nv\", \"inst3_2d_gas_Nx\", \"inst6_3d_ana_Np\", \"inst6_3d_ana_Nv\", \"statD_2d_slv_Nx\", \"tavg1_2d_adg_Nx\", \"tavg1_2d_aer_Nx\", \"tavg1_2d_chm_Nx\", \"tavg1_2d_csp_Nx\", \"tavg1_2d_flx_Nx\", \"tavg1_2d_int_Nx\", \"tavg1_2d_lfo_Nx\", \"tavg1_2d_lnd_Nx\", \"tavg1_2d_ocn_Nx\", \"tavg1_2d_rad_Nx\", \"tavg1_2d_slv_Nx\", \"tavg3_3d_mst_Ne\", \"tavg3_3d_trb_Ne\", \"tavg3_3d_nav_Ne\", \"tavg3_3d_cld_Np\", \"tavg3_3d_mst_Np\", \"tavg3_3d_rad_Np\", \"tavg3_3d_tdt_Np\", \"tavg3_3d_trb_Np\", \"tavg3_3d_udt_Np\", \"tavg3_3d_odt_Np\", \"tavg3_3d_qdt_Np\", \"tavg3_3d_asm_Nv\", \"tavg3_3d_cld_Nv\", \"tavg3_3d_mst_Nv\", \"tavg3_3d_rad_Nv\", \"tavg3_2d_glc_Nx\"), directory_to_save = NULL, data_download_acknowledgement = FALSE, download = FALSE, remove_command = FALSE )"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_merra2_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download meteorological and atmospheric data from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) model. — download_merra2_data","text":"date_start character(1). length 10. Start date downloading data. Format YYYY-MM-DD (ex. September 1, 2023 \"2023-09-01\"). date_end character(1). length 10. End date downloading data. Format YYYY-MM-DD (ex. September 1, 2023 \"2023-09-01\"). collection character(1). MERRA-2 data collection file name. directory_to_save character(1). Directory save data. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_merra2_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download meteorological and atmospheric data from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) model. — download_merra2_data","text":"NULL;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_merra2_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download meteorological and atmospheric data from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) model. — download_merra2_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_modis_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download MODIS product files — download_modis_data","title":"Download MODIS product files — download_modis_data","text":"Need maintenance directory path change NASA EOSDIS. function first retrieves hdf download links certain day, selects relevant tiles retrieved links. Download done queried horizontal-vertical tile number combinations. exception MOD06_L2 product, produced every five minutes every day.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_modis_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download MODIS product files — download_modis_data","text":"","code":"download_modis_data( date_start = \"2023-09-01\", date_end = \"2023-09-01\", product = c(\"MOD09GA\", \"MOD11A1\", \"MOD06_L2\", \"MCD19A2\", \"MOD13A2\", \"VNP46A2\"), version = \"61\", horizontal_tiles = c(7, 13), vertical_tiles = c(3, 6), nasa_earth_data_token = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, mod06_links = NULL, download = TRUE, remove_command = FALSE )"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_modis_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download MODIS product files — download_modis_data","text":"date_start character(1). length 10. Start date downloading data. Format YYYY-MM-DD (ex. September 1, 2023 \"2023-09-01\"). date_end character(1). length 10. End date downloading data. Format YYYY-MM-DD (ex. September 1, 2023 \"2023-09-01\"). product character(1). One c(\"MOD09GA\", \"MOD11A1\", \"MOD06_L2\", \"MCD19A2\", \"MOD13A2\", \"VNP46A2\") version character(1). Default \"61\", meaning v061. horizontal_tiles integer(2). Horizontal tile numbers c({start}, {end}). Default c(7, 13). vertical_tiles integer(2). Vertical tile numbers c({start}, {end}). Default c(3, 6). nasa_earth_data_token character(1). Token downloading data NASA. set trying running function. directory_to_save character(1). Directory save data. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. mod06_links character(1). CSV file path MOD06_L2 download links NASA LPDAAC. Default NULL. download logical(1). Download data save wget commands. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_modis_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download MODIS product files — download_modis_data","text":"NULL;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_modis_data.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Download MODIS product files — download_modis_data","text":"date_start date_end year. Directory structure looks like input/modis/raw/{version}/{product}/{year}/{day_of_year} Please note date_start date_end ignored product == 'MOD06_L2'.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_modis_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download MODIS product files — download_modis_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_narr_monolevel_data.html","id":null,"dir":"Reference","previous_headings":"","what":"download_narr_monolevel_data: download monolevel meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_monolevel_data","title":"download_narr_monolevel_data: download monolevel meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_monolevel_data","text":"download_narr_monolevel_data function accesses downloads monolevel meteorological data NOAA NCEP North American Regional Reanalysis (NARR).","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_narr_monolevel_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"download_narr_monolevel_data: download monolevel meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_monolevel_data","text":"","code":"download_narr_monolevel_data( year_start = 2022, year_end = 2022, variables = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, download = FALSE, remove_command = FALSE )"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_narr_monolevel_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"download_narr_monolevel_data: download monolevel meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_monolevel_data","text":"year_start integer(1). length 4. Start year range downloading data. year_end integer(1). length 4. End year range downloading data. variables character. Variable(s) name acronym. directory_to_save character(1). Directory(s) save downloaded data files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_narr_monolevel_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"download_narr_monolevel_data: download monolevel meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_monolevel_data","text":"NULL;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_narr_monolevel_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"download_narr_monolevel_data: download monolevel meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_monolevel_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_narr_p_levels_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download pressure level meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_p_levels_data","title":"Download pressure level meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_p_levels_data","text":"download_narr_p_levels_data function accesses downloads pressure level meteorological data NOAA NCEP North American Regional Reanalysis (NARR).","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_narr_p_levels_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download pressure level meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_p_levels_data","text":"","code":"download_narr_p_levels_data( year_start = 2022, year_end = 2022, variables = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, download = FALSE, remove_command = FALSE )"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_narr_p_levels_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download pressure level meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_p_levels_data","text":"year_start integer(1). length 4. Start year range downloading data. year_end integer(1). length 4. End year range downloading data. variables character(1). Variable(s) name acronym. directory_to_save character(1). Directory(s) save downloaded data files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_narr_p_levels_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download pressure level meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_p_levels_data","text":"NULL;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_narr_p_levels_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download pressure level meteorological data from NOAA NCEP North American Regional Reanalysis (NARR) model. — download_narr_p_levels_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_nei_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download data from EPA National Emission Inventory aggregated on-road emission data — download_nei_data","title":"Download data from EPA National Emission Inventory aggregated on-road emission data — download_nei_data","text":"Download data EPA National Emission Inventory aggregated -road emission data","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_nei_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download data from EPA National Emission Inventory aggregated on-road emission data — download_nei_data","text":"","code":"download_nei_data( directory_to_save = NULL, data_download_acknowledgement = FALSE, download = FALSE, remove_command = FALSE, year_target = c(2017L, 2020L), unzip = FALSE, epa_certificate_path = system.file(\"extdata/cacert_gaftp_epa.pem\", package = \"amadeus\"), certificate_url = \"http://cacerts.digicert.com/DigiCertGlobalG2TLSRSASHA2562020CA1-1.crt\" )"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_nei_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download data from EPA National Emission Inventory aggregated on-road emission data — download_nei_data","text":"directory_to_save character(1). Directory download files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands. year_target Available years NEI data. Default c(2017L, 2020L). unzip logical(1). Unzip downloaded zip files. Default FALSE. epa_certificate_path character(1). Path certificate file EPA DataCommons. Default 'extdata/cacert_gaftp_epa.pem' package installation path. certificate_url character(1). URL certificate file. See notes details.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_nei_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download data from EPA National Emission Inventory aggregated on-road emission data — download_nei_data","text":"NULL; Two comma-separated value (CSV) raw files 2017 2020","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_nei_data.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Download data from EPA National Emission Inventory aggregated on-road emission data — download_nei_data","text":"EPA Data Commons certificate errors, follow steps : Click Lock icon address bar https://gaftp.epa.gov Click Show Certificate Access Details Find URL *.crt extension Currently bundle pre-downloaded crt PEM (accepted wget command) file ./inst/extdata. instruction certificate updates future.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_nei_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download data from EPA National Emission Inventory aggregated on-road emission data — download_nei_data","text":"Ranadeep Daw, Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_nlcd_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download land cover data from the National Land Cover Database Science Research Products. — download_nlcd_data","title":"Download land cover data from the National Land Cover Database Science Research Products. — download_nlcd_data","text":"download_nlcd_data() function accesses downloads land cover data NLCD Science Research Products data base.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_nlcd_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download land cover data from the National Land Cover Database Science Research Products. — download_nlcd_data","text":"","code":"download_nlcd_data( year = 2021, collection = \"Coterminous United States\", directory_to_download = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, unzip = TRUE, remove_zip = FALSE, download = FALSE, remove_command = FALSE )"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_nlcd_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download land cover data from the National Land Cover Database Science Research Products. — download_nlcd_data","text":"year integer(1). Available years Coterminous United States include 2001, 2004, 2006, 2008, 2011, 2013, 2016, 2019, 2021. Available years Alaska include 2001, 2011, 2016. collection character(1). \"Coterminous United States\" \"Alaska\". directory_to_download character(1). Directory download zip files National Land Cover Database Science Research Products. directory_to_save character(1). Directory decompress zip files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. unzip logical(1). Unzip zip files. Default TRUE. remove_zip logical(1). Remove zip files directory_to_download. Default FALSE. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_nlcd_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download land cover data from the National Land Cover Database Science Research Products. — download_nlcd_data","text":"NULL;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_nlcd_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download land cover data from the National Land Cover Database Science Research Products. — download_nlcd_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_permit.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for data download acknowledgement — download_permit","title":"Check for data download acknowledgement — download_permit","text":"Check data download acknowledgement","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_permit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for data download acknowledgement — download_permit","text":"","code":"download_permit(data_download_acknowledgement)"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_permit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for data download acknowledgement — download_permit","text":"data_download_acknowledgement logical(1). Whether start downloading","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_remove_command.html","id":null,"dir":"Reference","previous_headings":"","what":"Remove or keep wget command file — download_remove_command","title":"Remove or keep wget command file — download_remove_command","text":"Remove keep wget command file","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_remove_command.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Remove or keep wget command file — download_remove_command","text":"","code":"download_remove_command(commands_txt = NULL, remove = FALSE)"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_remove_command.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Remove or keep wget command file — download_remove_command","text":"commands_txt character(1). Path download commands remove logical(1). Remove (TRUE) keep (FALSE) commands","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_remove_zips.html","id":null,"dir":"Reference","previous_headings":"","what":"Remove downloaded zip files — download_remove_zips","title":"Remove downloaded zip files — download_remove_zips","text":"Remove downloaded zip files","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_remove_zips.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Remove downloaded zip files — download_remove_zips","text":"","code":"download_remove_zips(remove = FALSE, download_name)"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_remove_zips.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Remove downloaded zip files — download_remove_zips","text":"remove logical(1). Confirm removal. Default FALSE. download_name character. Full zip file path","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_run.html","id":null,"dir":"Reference","previous_headings":"","what":"download_run: execute or skip system_command\nin data download function. — download_run","title":"download_run: execute or skip system_command\nin data download function. — download_run","text":"Execute skip commands listed ...wget/curl_commands.txt file produced one data download functions.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_run.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"download_run: execute or skip system_command\nin data download function. — download_run","text":"","code":"download_run(download = FALSE, system_command = NULL)"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_run.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"download_run: execute or skip system_command\nin data download function. — download_run","text":"download logical(1). Execute (TRUE) skip (FALSE) download. system_command character(1). Linux command execute downloads. Inherited data download function.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_sanitize_path.html","id":null,"dir":"Reference","previous_headings":"","what":"Sanitize path to end with a forward slash — download_sanitize_path","title":"Sanitize path to end with a forward slash — download_sanitize_path","text":"Sanitize path end forward slash","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_sanitize_path.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Sanitize path to end with a forward slash — download_sanitize_path","text":"","code":"download_sanitize_path(directory)"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_sanitize_path.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Sanitize path to end with a forward slash — download_sanitize_path","text":"directory character(1). Path","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_sanitize_path.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Sanitize path to end with a forward slash — download_sanitize_path","text":"character ending forward slash.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_sedac_groads_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download Global Roads Open Access Data Set (gROADS), v1 (1980-2010) data from NASA Socioeconomic Data and Applications Center (SEDAC). — download_sedac_groads_data","title":"Download Global Roads Open Access Data Set (gROADS), v1 (1980-2010) data from NASA Socioeconomic Data and Applications Center (SEDAC). — download_sedac_groads_data","text":"download_sedac_groads_data() function accesses downloads roads data National Aeronautics Space Administration's (NASA) Global Roads Open Access Data Set.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_sedac_groads_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download Global Roads Open Access Data Set (gROADS), v1 (1980-2010) data from NASA Socioeconomic Data and Applications Center (SEDAC). — download_sedac_groads_data","text":"","code":"download_sedac_groads_data( data_format = c(\"Shapefile\", \"Geodatabase\"), data_region = c(\"Americas\", \"Global\", \"Africa\", \"Asia\", \"Europe\", \"Oceania East\", \"Oceania West\"), directory_to_download = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, unzip = TRUE, remove_zip = FALSE, download = FALSE, remove_command = FALSE )"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_sedac_groads_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download Global Roads Open Access Data Set (gROADS), v1 (1980-2010) data from NASA Socioeconomic Data and Applications Center (SEDAC). — download_sedac_groads_data","text":"data_format character(1). Data can downloaded \"Shapefile\" \"Geodatabase\". (\"Geodatabase\" available \"Global\" region). data_region character(1). Data can downloaded \"Global\", \"Africa\", \"Asia\", \"Europe\", \"Americas\", \"Oceania East\", \"Oceania West\". directory_to_download character(1). Directory download zip files NASA Global Roads Open Access Data Set. directory_to_save character(1). Directory decompress zip files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. unzip logical(1). Unzip zip files. Default TRUE. remove_zip logical(1). Remove zip files directory_to_download. Default FALSE. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_sedac_groads_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download Global Roads Open Access Data Set (gROADS), v1 (1980-2010) data from NASA Socioeconomic Data and Applications Center (SEDAC). — download_sedac_groads_data","text":"NULL;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_sedac_groads_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download Global Roads Open Access Data Set (gROADS), v1 (1980-2010) data from NASA Socioeconomic Data and Applications Center (SEDAC). — download_sedac_groads_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_sedac_population_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download UN WPP-Adjusted population density data from NASA Socioeconomic Data and Applications Center (SEDAC) — download_sedac_population_data","title":"Download UN WPP-Adjusted population density data from NASA Socioeconomic Data and Applications Center (SEDAC) — download_sedac_population_data","text":"download_sedac_population_data() function accesses downloads population density data National Aeronatuics Space Administration's (NASA) UN WPP-Adjusted Population Density, v4.11.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_sedac_population_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download UN WPP-Adjusted population density data from NASA Socioeconomic Data and Applications Center (SEDAC) — download_sedac_population_data","text":"","code":"download_sedac_population_data( year = \"2020\", data_format = c(\"GeoTIFF\", \"ASCII\", \"netCDF\"), data_resolution = \"60 minute\", directory_to_download = NULL, directory_to_save = NULL, data_download_acknowledgement = FALSE, download = FALSE, unzip = TRUE, remove_zip = FALSE, remove_command = FALSE )"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_sedac_population_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download UN WPP-Adjusted population density data from NASA Socioeconomic Data and Applications Center (SEDAC) — download_sedac_population_data","text":"year character(1). Available years 2000, 2005, 2010, 2015, 2020, \"\" years. data_format character(1). Individual year data can downloaded \"ASCII\" \"GeoTIFF\". \"\" years downloaded \"netCDF\". data_resolution character(1). Available resolutions 30 second (approx. 1 km), 2.5 minute (approx. 5 km), 15 minute (approx. 30 km), 30 minute (approx. 55 km), 60 minute (approx. 110 km). directory_to_download character(1). Directory download zip files NASA UN WPP-Adjusted Population Density, v4.11. directory_to_save character(1). Directory decompress zip files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. unzip logical(1). Unzip zip files. Default TRUE. remove_zip logical(1). Remove zip files directory_to_download. Default FALSE. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_sedac_population_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download UN WPP-Adjusted population density data from NASA Socioeconomic Data and Applications Center (SEDAC) — download_sedac_population_data","text":"NULL;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_sedac_population_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download UN WPP-Adjusted population density data from NASA Socioeconomic Data and Applications Center (SEDAC) — download_sedac_population_data","text":"Mitchell Manware, Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_setup_dir.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if input directory exists — download_setup_dir","title":"Check if input directory exists — download_setup_dir","text":"directory exist, directory created.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_setup_dir.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if input directory exists — download_setup_dir","text":"","code":"download_setup_dir(directory)"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_setup_dir.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if input directory exists — download_setup_dir","text":"directory character(1) directory path","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_sink.html","id":null,"dir":"Reference","previous_headings":"","what":"Start sink download commands into a text file — download_sink","title":"Start sink download commands into a text file — download_sink","text":"Start sink download commands text file","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_sink.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Start sink download commands into a text file — download_sink","text":"","code":"download_sink(command_txt)"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_sink.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Start sink download commands into a text file — download_sink","text":"command_txt character(1). file path export commands.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_tri_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download data from EPA toxic release inventory — download_tri_data","title":"Download data from EPA toxic release inventory — download_tri_data","text":"Download data EPA toxic release inventory","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_tri_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download data from EPA toxic release inventory — download_tri_data","text":"","code":"download_tri_data( year_start = 2018L, year_end = 2022L, directory_to_save = NULL, data_download_acknowledgement = FALSE, download = FALSE, remove_command = FALSE )"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_tri_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download data from EPA toxic release inventory — download_tri_data","text":"year_start integer(1). length 4. Start year downloading data. year_end integer(1). length 4. End year downloading data. directory_to_save character(1). Directory download files. data_download_acknowledgement logical(1). setting TRUE user acknowledge data downloaded using function may large use lots machine storage memory. download logical(1). FALSE generate *.txt file containing download commands. setting TRUE function download requested data files. remove_command logical(1). Remove (TRUE) keep (FALSE) text file containing download commands.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_tri_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download data from EPA toxic release inventory — download_tri_data","text":"NULL; Yearly comma-separated value (CSV) raw files year","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_tri_data.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Download data from EPA toxic release inventory — download_tri_data","text":"Mariana Kassien, Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_unzip.html","id":null,"dir":"Reference","previous_headings":"","what":"Unzip downloaded data — download_unzip","title":"Unzip downloaded data — download_unzip","text":"Unzip downloaded data","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/download_unzip.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Unzip downloaded data — download_unzip","text":"","code":"download_unzip(file_name, directory_to_unzip, unzip = TRUE)"},{"path":"https://kyle-messier.github.io/amadeus/reference/download_unzip.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Unzip downloaded data — download_unzip","text":"file_name character(1). Full zip file path directory_to_unzip character(1). Directory unzip data unzip logical(1). Unzip (TRUE) .","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/dt_as_mysftime.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a sftime from a datatable — dt_as_mysftime","title":"Create a sftime from a datatable — dt_as_mysftime","text":"Create sftime datatable","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/dt_as_mysftime.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a sftime from a datatable — dt_as_mysftime","text":"","code":"dt_as_mysftime(x, lonname, latname, timename, crs)"},{"path":"https://kyle-messier.github.io/amadeus/reference/dt_as_mysftime.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a sftime from a datatable — dt_as_mysftime","text":"x data.table lonname character longitude column name latname character latitude column name timename character time column name crs coordinate reference system","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/dt_as_mysftime.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a sftime from a datatable — dt_as_mysftime","text":"sftime object","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/dt_as_mysftime.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Create a sftime from a datatable — dt_as_mysftime","text":"Eva Marques","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/extract_urls.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract URLs from download commands — extract_urls","title":"Extract URLs from download commands — extract_urls","text":"Extract URLs download commands","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/extract_urls.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract URLs from download commands — extract_urls","text":"","code":"extract_urls(commands = commands, position = NULL)"},{"path":"https://kyle-messier.github.io/amadeus/reference/extract_urls.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract URLs from download commands — extract_urls","text":"commands character vector containing download commands position URL position vector","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/extract_urls.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract URLs from download commands — extract_urls","text":"character vector containing download URLs","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/generate_date_sequence.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate sequence of dates based on date_start and date_end. — generate_date_sequence","title":"Generate sequence of dates based on date_start and date_end. — generate_date_sequence","text":"Generate sequence dates based date_start date_end.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/generate_date_sequence.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate sequence of dates based on date_start and date_end. — generate_date_sequence","text":"","code":"generate_date_sequence(date_start, date_end, sub_hyphen = TRUE)"},{"path":"https://kyle-messier.github.io/amadeus/reference/generate_date_sequence.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate sequence of dates based on date_start and date_end. — generate_date_sequence","text":"date_start character(1). Beginning date sequence. date_end character(1). End date sequence. sub_hyphen logical(1). Substitute hyphen dates. TRUE, returns date sequence \"YYYYMMDD\". FALSE, returns date sequence \"YYYY-MM-DD\".","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/generate_date_sequence.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate sequence of dates based on date_start and date_end. — generate_date_sequence","text":"vector","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/generate_time_sequence.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate time sequence based on GEOS-CF data collection. — generate_time_sequence","title":"Generate time sequence based on GEOS-CF data collection. — generate_time_sequence","text":"Generate time sequence based GEOS-CF data collection.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/generate_time_sequence.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate time sequence based on GEOS-CF data collection. — generate_time_sequence","text":"","code":"generate_time_sequence(collection)"},{"path":"https://kyle-messier.github.io/amadeus/reference/generate_time_sequence.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate time sequence based on GEOS-CF data collection. — generate_time_sequence","text":"collection character(1). GEOS-CF data collection","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/generate_time_sequence.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate time sequence based on GEOS-CF data collection. — generate_time_sequence","text":"vector","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/is_date_proper.html","id":null,"dir":"Reference","previous_headings":"","what":"Check input strings conform to the required format — is_date_proper","title":"Check input strings conform to the required format — is_date_proper","text":"Check input strings conform required format","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/is_date_proper.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check input strings conform to the required format — is_date_proper","text":"","code":"is_date_proper(instr = NULL, format = \"%Y-%m-%d\")"},{"path":"https://kyle-messier.github.io/amadeus/reference/is_date_proper.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check input strings conform to the required format — is_date_proper","text":"instr character(1). String check. format character(1). Matching format checked. Default \"%Y-%m-%d\", can detect \"%Y/%m/%d. See strftime details formatting string.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/is_date_proper.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check input strings conform to the required format — is_date_proper","text":"returning value. stops function instr conform format.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/is_date_proper.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Check input strings conform to the required format — is_date_proper","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_aqs.html","id":null,"dir":"Reference","previous_headings":"","what":"Filter unique AQS sites with or without temporal information — process_aqs","title":"Filter unique AQS sites with or without temporal information — process_aqs","text":"Filter unique AQS sites without temporal information","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_aqs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filter unique AQS sites with or without temporal information — process_aqs","text":"","code":"process_aqs( path = NULL, date = c(\"2018-01-01\", \"2022-12-31\"), return_format = \"terra\" )"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_aqs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filter unique AQS sites with or without temporal information — process_aqs","text":"path character(1). Directory path daily measurement data. date character(2). Start end date. \"YYYY-MM-DD\" format sorted. NULL, unique locations returned. return_format character(1). \"terra\" \"sf\".","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_aqs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filter unique AQS sites with or without temporal information — process_aqs","text":"SpatVector sf object depending return_format.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_aqs.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Filter unique AQS sites with or without temporal information — process_aqs","text":"date = NULL return massive data.table object. Please choose proper date values.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_bluemarble.html","id":null,"dir":"Reference","previous_headings":"","what":"Assign VIIRS Blue Marble products corner coordinates to retrieve a merged raster — process_bluemarble","title":"Assign VIIRS Blue Marble products corner coordinates to retrieve a merged raster — process_bluemarble","text":"function return SpatRaster object georeferenced h5 files Blue Marble product. Referencing corner coordinates necessary original h5 data include information.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_bluemarble.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assign VIIRS Blue Marble products corner coordinates to retrieve a merged raster — process_bluemarble","text":"","code":"process_bluemarble( path = NULL, date = NULL, tile_df = process_bluemarble_corners(), subdataset = 3L, crs = \"EPSG:4326\", ... )"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_bluemarble.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assign VIIRS Blue Marble products corner coordinates to retrieve a merged raster — process_bluemarble","text":"path character. Full paths h5 files. date character(1). Date query. tile_df data.frame. Contains four corner coordinates fields named c(\"xmin\", \"xmax\", \"ymin\", \"ymax\"). See process_bluemarble_corners generate valid object argument. subdataset integer(1). Subdataset number process. Default 3L. crs character(1). terra::crs compatible CRS. Default \"EPSG:4326\" ... internal use.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_bluemarble.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assign VIIRS Blue Marble products corner coordinates to retrieve a merged raster — process_bluemarble","text":"SpatRaster.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_bluemarble.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Assign VIIRS Blue Marble products corner coordinates to retrieve a merged raster — process_bluemarble","text":"Wang, Z. (2022). Blue Marble User Guide (Version 1.3). NASA.","code":""},{"path":[]},{"path":"https://kyle-messier.github.io/amadeus/reference/process_bluemarble.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Assign VIIRS Blue Marble products corner coordinates to retrieve a merged raster — process_bluemarble","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_bluemarble_corners.html","id":null,"dir":"Reference","previous_headings":"","what":"Tile corner generator for Blue Marble products — process_bluemarble_corners","title":"Tile corner generator for Blue Marble products — process_bluemarble_corners","text":"Blue Marble products HDF5 format read without georeference typical R geospatial packages. function generates data.frame corner coordinates assignment.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_bluemarble_corners.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tile corner generator for Blue Marble products — process_bluemarble_corners","text":"","code":"process_bluemarble_corners(hrange = c(5, 11), vrange = c(3, 6))"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_bluemarble_corners.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tile corner generator for Blue Marble products — process_bluemarble_corners","text":"hrange integer(2). 0-35. vrange integer(2). 0-17.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_bluemarble_corners.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tile corner generator for Blue Marble products — process_bluemarble_corners","text":"data.frame xmin, xmax, ymin, ymax fields.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_bluemarble_corners.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Tile corner generator for Blue Marble products — process_bluemarble_corners","text":"Wang, Z. (2022). Blue Marble User Guide (Version 1.3). NASA.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_bluemarble_corners.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tile corner generator for Blue Marble products — process_bluemarble_corners","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_conformity.html","id":null,"dir":"Reference","previous_headings":"","what":"Check input assumptions — process_conformity","title":"Check input assumptions — process_conformity","text":"Check \"lon\", \"lat\", \"time\" (check_time = TRUE) convert inputs SpatVector object.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_conformity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check input assumptions — process_conformity","text":"","code":"process_conformity(locs = NULL, check_time = FALSE, locs_epsg = \"EPSG:4326\")"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_conformity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check input assumptions — process_conformity","text":"locs Data. sf, SpatVector, data.frame check_time logical(1). Whether \"time\" exists column names. locs_epsg character(1). \"{authority}:{code}\" Well-Known Text format coordinate reference system definition.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_conformity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check input assumptions — process_conformity","text":"SpatVector object.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_conformity.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Check input assumptions — process_conformity","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_covariates.html","id":null,"dir":"Reference","previous_headings":"","what":"Process covariates — process_covariates","title":"Process covariates — process_covariates","text":"Process covariates","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_covariates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Process covariates — process_covariates","text":"","code":"process_covariates( covariate = c(\"modis_swath\", \"modis_merge\", \"koppen-geiger\", \"bluemarble\", \"koeppen-geiger\", \"koppen\", \"koeppen\", \"geos\", \"dummies\", \"gmted\", \"hms\", \"smoke\", \"sedac_population\", \"population\", \"sedac_groads\", \"groads\", \"roads\", \"nlcd\", \"tri\", \"narr\", \"nei\", \"ecoregions\", \"ecoregion\"), path = NULL, ... )"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_covariates.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Process covariates — process_covariates","text":"covariate character(1). Covariate type. path character(1). Directory file path raw data depending covariate value. ... Arguments passed raw data processing function.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_covariates.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Process covariates — process_covariates","text":"SpatVector SpatRaster depending covariate type.","code":""},{"path":[]},{"path":"https://kyle-messier.github.io/amadeus/reference/process_covariates.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Process covariates — process_covariates","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_ecoregion.html","id":null,"dir":"Reference","previous_headings":"","what":"Process EPA Ecoregion shapefiles — process_ecoregion","title":"Process EPA Ecoregion shapefiles — process_ecoregion","text":"Process EPA Ecoregion shapefiles","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_ecoregion.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Process EPA Ecoregion shapefiles — process_ecoregion","text":"","code":"process_ecoregion(path = NULL)"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_ecoregion.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Process EPA Ecoregion shapefiles — process_ecoregion","text":"path character(1). Path Ecoregion Shapefiles","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_ecoregion.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Process EPA Ecoregion shapefiles — process_ecoregion","text":"SpatVector object.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_ecoregion.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Process EPA Ecoregion shapefiles — process_ecoregion","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_flatten_sds.html","id":null,"dir":"Reference","previous_headings":"","what":"Aggregate layers in a sub-dataset in sinusoidal MODIS products — process_flatten_sds","title":"Aggregate layers in a sub-dataset in sinusoidal MODIS products — process_flatten_sds","text":"MODIS products consist multi-layer subdatasets. function aggregates multiple layers single layer SpatRaster. fun_agg applied overlapping cells.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_flatten_sds.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Aggregate layers in a sub-dataset in sinusoidal MODIS products — process_flatten_sds","text":"","code":"process_flatten_sds(path = NULL, subdataset = NULL, fun_agg = \"mean\")"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_flatten_sds.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Aggregate layers in a sub-dataset in sinusoidal MODIS products — process_flatten_sds","text":"path character(1). Full path MODIS HDF4/HDF5 file. Direct sub-dataset access supported, example, HDF4_EOS:EOS_GRID:{filename}:{base_grid_information}:{sub-dataset} subdataset character(1). Exact regular expression filter sub-dataset. See process_modis_sds details. fun_agg character(1). Function name aggregate layers. acceptable terra::tapp.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_flatten_sds.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Aggregate layers in a sub-dataset in sinusoidal MODIS products — process_flatten_sds","text":"SpatRaster.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_flatten_sds.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Aggregate layers in a sub-dataset in sinusoidal MODIS products — process_flatten_sds","text":"HDF values read original without scaling. Users consult MODIS product documentation apply proper scaling factor post-hoc adjustment. users preliminary information MODIS sub-datasets, consider running terra::describe(__filename__, sds = TRUE) navigate full list sub-datasets input file consult documentation MODIS product.","code":""},{"path":[]},{"path":"https://kyle-messier.github.io/amadeus/reference/process_flatten_sds.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Aggregate layers in a sub-dataset in sinusoidal MODIS products — process_flatten_sds","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_geos.html","id":null,"dir":"Reference","previous_headings":"","what":"Import and clean GEOS-CF data downloaded with\ndownload_geos_data or download_data(dataset_name = ","title":"Import and clean GEOS-CF data downloaded with\ndownload_geos_data or download_data(dataset_name = ","text":"Import clean GEOS-CF data downloaded download_geos_data download_data(dataset_name = \"geos\"). Function returns SpatRast object containing user-defined variables interest. Layer names indicate variable, pressure level, date (YYYYMMDD), , applicable, hour (HHMMSS).","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_geos.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import and clean GEOS-CF data downloaded with\ndownload_geos_data or download_data(dataset_name = ","text":"","code":"process_geos( date = c(\"2018-01-01\", \"2018-01-01\"), variable = NULL, path = NULL )"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_geos.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import and clean GEOS-CF data downloaded with\ndownload_geos_data or download_data(dataset_name = ","text":"date character(2). length 10. Format \"YYYY-MM-DD\". variable character(1). GEOS-CF variable name(s). path character(1). Directory downloaded GEOS-CF netCDF files.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_geos.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import and clean GEOS-CF data downloaded with\ndownload_geos_data or download_data(dataset_name = ","text":"SpatRaster object;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_geos.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Import and clean GEOS-CF data downloaded with\ndownload_geos_data or download_data(dataset_name = ","text":"Mitchell Manware","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_geos_collection.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify GEOS-CF collection based on user-defined file paths — process_geos_collection","title":"Identify GEOS-CF collection based on user-defined file paths — process_geos_collection","text":"Identify GEOS-CF collection based user-defined file paths","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_geos_collection.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify GEOS-CF collection based on user-defined file paths — process_geos_collection","text":"","code":"process_geos_collection( path, collection = FALSE, date = FALSE, datetime = FALSE )"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_geos_collection.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify GEOS-CF collection based on user-defined file paths — process_geos_collection","text":"path character(1). File path GEOS-CF data file. collection logical(1). Identifies returns GEOS-CF collection name(s) based provided file path(s). date logical(1). Identifies returns date sequence (YYYYMMDD) based provided file path(s). datetime logical(1). Identifies returns date time sequence (YYYYMoMoDDHHMiMi) based provided file path(s).","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_geos_collection.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify GEOS-CF collection based on user-defined file paths — process_geos_collection","text":"character","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_gmted.html","id":null,"dir":"Reference","previous_headings":"","what":"Import and clean Global Multi-resolution Terrain Elevation Data (GMTED2010)\ndownloaded with download_gmted or download_data(dataset_name = ","title":"Import and clean Global Multi-resolution Terrain Elevation Data (GMTED2010)\ndownloaded with download_gmted or download_data(dataset_name = ","text":"Import clean Global Multi-resolution Terrain Elevation Data (GMTED2010) downloaded download_gmted download_data(dataset_name = \"gmted\"). Function returns SpatRast object containing user-defined variable interest specified resolution. Layer name indicates variable resolution.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_gmted.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import and clean Global Multi-resolution Terrain Elevation Data (GMTED2010)\ndownloaded with download_gmted or download_data(dataset_name = ","text":"","code":"process_gmted(variable = NULL, path = NULL)"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_gmted.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import and clean Global Multi-resolution Terrain Elevation Data (GMTED2010)\ndownloaded with download_gmted or download_data(dataset_name = ","text":"variable vector(1). Vector containing GMTED statistic first resolution second. (Example: variable = c(\"Breakline Emphasis\", \"7.5 arc-seconds\")). path character(1). Directory downloaded GEOS-CF \"*_grd\" folder containing .adf files.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_gmted.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import and clean Global Multi-resolution Terrain Elevation Data (GMTED2010)\ndownloaded with download_gmted or download_data(dataset_name = ","text":"SpatRaster object","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_gmted.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Import and clean Global Multi-resolution Terrain Elevation Data (GMTED2010)\ndownloaded with download_gmted or download_data(dataset_name = ","text":"Mitchell Manware","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_gmted_codes.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate statistic and resolution codes based on GMTED statistic and\nresolution. — process_gmted_codes","title":"Generate statistic and resolution codes based on GMTED statistic and\nresolution. — process_gmted_codes","text":"Generate statistic resolution codes based GMTED statistic resolution.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_gmted_codes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate statistic and resolution codes based on GMTED statistic and\nresolution. — process_gmted_codes","text":"","code":"process_gmted_codes( string, statistic = FALSE, resolution = FALSE, invert = FALSE )"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_gmted_codes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate statistic and resolution codes based on GMTED statistic and\nresolution. — process_gmted_codes","text":"string character(1). File path GEOS-CF data file. statistic logical(1). Matches statistic statistic code. resolution logical(1). Matches resolution resolution code. invert logical(1). Default = FALSE. invert = TRUE assumes string provides statistic resolution code, returns full length statistic resolution.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_gmted_codes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate statistic and resolution codes based on GMTED statistic and\nresolution. — process_gmted_codes","text":"character","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_hms.html","id":null,"dir":"Reference","previous_headings":"","what":"Import and clean wildfire smoke plume coverage data from NOAA Hazard\nMapping System Fire and Smoke Product. — process_hms","title":"Import and clean wildfire smoke plume coverage data from NOAA Hazard\nMapping System Fire and Smoke Product. — process_hms","text":"Import clean wildfire smoke plume coverage data NOAA Hazard Mapping System Fire Smoke Product.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_hms.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import and clean wildfire smoke plume coverage data from NOAA Hazard\nMapping System Fire and Smoke Product. — process_hms","text":"","code":"process_hms( date = c(\"2018-01-01\", \"2018-01-01\"), variable = c(\"Light\", \"Medium\", \"Heavy\"), path = NULL )"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_hms.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import and clean wildfire smoke plume coverage data from NOAA Hazard\nMapping System Fire and Smoke Product. — process_hms","text":"date character(2). length 10 . Start/end date downloaded data. Format YYYY-MM-DD (ex. September 1, 2023 = \"2023-09-01\"). variable character(1). \"Light\", \"Medium\", \"Heavy\". path character(1). Directory downloaded NOAA HMS data files.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_hms.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import and clean wildfire smoke plume coverage data from NOAA Hazard\nMapping System Fire and Smoke Product. — process_hms","text":"SpatVector object;","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_hms.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Import and clean wildfire smoke plume coverage data from NOAA Hazard\nMapping System Fire and Smoke Product. — process_hms","text":"Mitchell Manware.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_koppen_geiger.html","id":null,"dir":"Reference","previous_headings":"","what":"Process Koeppen-Geiger climate data — process_koppen_geiger","title":"Process Koeppen-Geiger climate data — process_koppen_geiger","text":"Process Koeppen-Geiger climate data","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_koppen_geiger.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Process Koeppen-Geiger climate data — process_koppen_geiger","text":"","code":"process_koppen_geiger(path = NULL, year = NULL)"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_koppen_geiger.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Process Koeppen-Geiger climate data — process_koppen_geiger","text":"path character(1). Path Koppen-Geiger climate zone raster file year data year. applicable function.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_koppen_geiger.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Process Koeppen-Geiger climate data — process_koppen_geiger","text":"SpatRaster object","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_koppen_geiger.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Process Koeppen-Geiger climate data — process_koppen_geiger","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_locs_radius.html","id":null,"dir":"Reference","previous_headings":"","what":"Create circular buffer around site points. — process_locs_radius","title":"Create circular buffer around site points. — process_locs_radius","text":"Creates circular buffer around points radius > 0. Returns points radius 0.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_locs_radius.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create circular buffer around site points. — process_locs_radius","text":"","code":"process_locs_radius(locs, radius)"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_locs_radius.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create circular buffer around site points. — process_locs_radius","text":"locs SpatVector(1). SpatVector object point geometry radius integer(1). Circular buffer size (meters).","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_locs_radius.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create circular buffer around site points. — process_locs_radius","text":"SpatVector.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_locs_vector.html","id":null,"dir":"Reference","previous_headings":"","what":"Import and prepare site point locations for covariate calculations. — process_locs_vector","title":"Import and prepare site point locations for covariate calculations. — process_locs_vector","text":"Import prepare site point locations covariate calculations.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_locs_vector.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import and prepare site point locations for covariate calculations. — process_locs_vector","text":"","code":"process_locs_vector(locs, crs, radius)"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_locs_vector.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import and prepare site point locations for covariate calculations. — process_locs_vector","text":"locs data.frame(1). Data frame containing columns unique identifier, latitute, longitude. Latitude longitude columns must named \"lat\" \"lon\", respectively. crs Coordinate reference system (CRS) description utilizing terra::crs(). radius integer(1). Circular buffer size (meters).","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_locs_vector.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import and prepare site point locations for covariate calculations. — process_locs_vector","text":"SpatVector","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_merge.html","id":null,"dir":"Reference","previous_headings":"","what":"Get mosaicked or merged raster from multiple MODIS hdf files — process_modis_merge","title":"Get mosaicked or merged raster from multiple MODIS hdf files — process_modis_merge","text":"Get mosaicked merged raster multiple MODIS hdf files","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_merge.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get mosaicked or merged raster from multiple MODIS hdf files — process_modis_merge","text":"","code":"process_modis_merge( path = NULL, date = NULL, subdataset = NULL, fun_agg = \"mean\", ... )"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_merge.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get mosaicked or merged raster from multiple MODIS hdf files — process_modis_merge","text":"path character. Full list hdf file paths. preferably recursive search result list.files. date character(1). date query. \"YYYY-MM-DD\" format. subdataset character(1). subdataset names extract. conform regular expression. See regex details. Default NULL, result errors. Users specify subdatasets imported. fun_agg Function name custom function aggregate overlapping cell values. See fun description tapp details. ... internal use.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_merge.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get mosaicked or merged raster from multiple MODIS hdf files — process_modis_merge","text":"SpatRaster object.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_merge.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Get mosaicked or merged raster from multiple MODIS hdf files — process_modis_merge","text":"Curvilinear products (.e., swaths) accepted. MODIS products downloaded functions amadeus, MODISTools, luna accepted.","code":""},{"path":[]},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_merge.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Get mosaicked or merged raster from multiple MODIS hdf files — process_modis_merge","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_sds.html","id":null,"dir":"Reference","previous_headings":"","what":"Selected MODIS sinusoidal grid product subdataset name selector — process_modis_sds","title":"Selected MODIS sinusoidal grid product subdataset name selector — process_modis_sds","text":"Four presets supported. custom_sel supersedes presets product values.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_sds.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Selected MODIS sinusoidal grid product subdataset name selector — process_modis_sds","text":"","code":"process_modis_sds( product = c(\"MOD11A1\", \"MOD13A2\", \"MOD09GA\", \"MCD19A2\"), custom_sel = NULL )"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_sds.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Selected MODIS sinusoidal grid product subdataset name selector — process_modis_sds","text":"product character(1). Product code. custom_sel character(1). Custom filter. value NULL, preset filter overridden.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_sds.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Selected MODIS sinusoidal grid product subdataset name selector — process_modis_sds","text":"character object conforms regular expression. Details regular expression R can found regexp.","code":""},{"path":[]},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_sds.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Selected MODIS sinusoidal grid product subdataset name selector — process_modis_sds","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_swath.html","id":null,"dir":"Reference","previous_headings":"","what":"Mosaic MODIS swaths — process_modis_swath","title":"Mosaic MODIS swaths — process_modis_swath","text":"function return SpatRaster object values selected subdatasets. Swath data include curvilinear grids, require warping/rectifying original curvilinear grids rectilinear grids. function internally warps inputs mosaic warped images one large SpatRaster object. Users need select subdataset process. full path looks like \"HDF4_EOS:EOS_SWATH:{file_path}:mod06:subdataset\", file_path full path hdf file.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_swath.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Mosaic MODIS swaths — process_modis_swath","text":"","code":"process_modis_swath( path = NULL, date = NULL, subdataset = c(\"Cloud_Fraction_Day\", \"Cloud_Fraction_Night\"), suffix = \":mod06:\", resolution = 0.025, ... )"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_swath.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Mosaic MODIS swaths — process_modis_swath","text":"path character. Full paths hdf files. date character(1). Date query. subdataset character. One \"Cloud_Fraction_Day\" \"Cloud_Fraction_Night\" (available MOD06_L2) suffix character(1). formatted :{product}:, e.g., :mod06: resolution numeric(1). Resolution output raster. Unit degree. ... internal use.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_swath.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Mosaic MODIS swaths — process_modis_swath","text":"SpatRaster object. CRS \"EPSG:4326\".","code":""},{"path":[]},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_swath.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Mosaic MODIS swaths — process_modis_swath","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_warp.html","id":null,"dir":"Reference","previous_headings":"","what":"Warp MODIS swath data into rectilinear grid raster — process_modis_warp","title":"Warp MODIS swath data into rectilinear grid raster — process_modis_warp","text":"Swath data type MODIS data, curvilinear points stored varying resolution depending relative position sensor axis. type data typically work well planar spatial data, users warp rectify data rectilinear raster. Main procedure done stars::st_warp, users able customize threshold fill potential gaps appear target resolution finer local resolution curvilinear grid points.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_warp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Warp MODIS swath data into rectilinear grid raster — process_modis_warp","text":"","code":"process_modis_warp( path = NULL, cellsize = 0.25, threshold = 0.5, crs = 4326, ... )"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_warp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Warp MODIS swath data into rectilinear grid raster — process_modis_warp","text":"path File path MODIS swath exact sub-dataset specification. cellsize numeric(1). Cell size (spatial resolution) output rectilinear grid raster. threshold numeric(1). Maximum distance fill gaps occur. crs integer(1)/character(1). Coordinate system definition. compatible EPSG codes WKT2. See terra::crs sf::st_crs / EPSG ... internal use.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_warp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Warp MODIS swath data into rectilinear grid raster — process_modis_warp","text":"stars object.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_warp.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Warp MODIS swath data into rectilinear grid raster — process_modis_warp","text":"Users specify sub-dataset flags compatible gdalinfo","code":""},{"path":[]},{"path":"https://kyle-messier.github.io/amadeus/reference/process_modis_warp.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Warp MODIS swath data into rectilinear grid raster — process_modis_warp","text":"Insang Song","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_narr.html","id":null,"dir":"Reference","previous_headings":"","what":"Import and clean NOAA NCEP North American Regional Reanalysis (NARR) data\ndownloaded with download_narr or download_data(dataset_name = ","title":"Import and clean NOAA NCEP North American Regional Reanalysis (NARR) data\ndownloaded with download_narr or download_data(dataset_name = ","text":"Import clean NOAA NCEP North American Regional Reanalysis (NARR) data downloaded download_narr download_data(dataset_name = \"NARR\"). Function returns SpatRast object containing user-defined variable interest. Layer names indicate variable, pressure level, date (YYYYMMDD).","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_narr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import and clean NOAA NCEP North American Regional Reanalysis (NARR) data\ndownloaded with download_narr or download_data(dataset_name = ","text":"","code":"process_narr( date = c(\"2023-09-01\", \"2023-09-01\"), variable = NULL, path = NULL )"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_narr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import and clean NOAA NCEP North American Regional Reanalysis (NARR) data\ndownloaded with download_narr or download_data(dataset_name = ","text":"date character(2). length 10 . Format \"YYYY-MM-DD\". variable character(1). NARR variable name(s). path character(1). Directory downloaded GEOS-CF netCDF files.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_narr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import and clean NOAA NCEP North American Regional Reanalysis (NARR) data\ndownloaded with download_narr or download_data(dataset_name = ","text":"SpatRaster object","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_narr.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Import and clean NOAA NCEP North American Regional Reanalysis (NARR) data\ndownloaded with download_narr or download_data(dataset_name = ","text":"Mitchell Manware","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_nei.html","id":null,"dir":"Reference","previous_headings":"","what":"Prepare National Emission Inventory CSV files — process_nei","title":"Prepare National Emission Inventory CSV files — process_nei","text":"NEI data comprises multiple csv files emissions 50+ pollutants recorded county level. raw data files, function join combined table NEI data county boundary, perform spatial join target locations.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_nei.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prepare National Emission Inventory CSV files — process_nei","text":"","code":"process_nei(path = NULL, county = NULL, year = c(2017, 2020))"},{"path":"https://kyle-messier.github.io/amadeus/reference/process_nei.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prepare National Emission Inventory CSV files — process_nei","text":"path character(1). Directory NEI csv files. county SpatVector/sf. County boundaries. year integer(1) Year use. Currently 2017 2020 accepted.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_nei.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prepare National Emission Inventory CSV files — process_nei","text":"SpatVector object.","code":""},{"path":"https://kyle-messier.github.io/amadeus/reference/process_nei.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Prepare National Emission Inventory CSV files — process_nei","text":"Base files county argument can downloaded directly U.S. Census Bureau using tigris package. function reproject census boundaries. 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index 5cee16cd..062daed0 100644
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