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docs: add a bit more about spatial data #176

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3 changes: 2 additions & 1 deletion R/emodnet_wfs.R
Original file line number Diff line number Diff line change
@@ -1,8 +1,9 @@
.emodnet_wfs <- function() {
utils::read.csv(
data <- utils::read.csv(
system.file("services.csv", package = "emodnet.wfs"),
stringsAsFactors = FALSE
)
tibble::as_tibble(data)
}
#' Available EMODnet Web Feature Services
#'
Expand Down
67 changes: 48 additions & 19 deletions README.Rmd
Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,7 @@ options(timeout = 2000)

The goal of emodnet.wfs is to allow interrogation of and access to [EMODnet's, European Marine Observation and Data Network, geographic vector data](https://emodnet.ec.europa.eu/en/emodnet-web-service-documentation#inline-nav-3) in R through the [EMODnet Web Feature Services](https://emodnet.ec.europa.eu/en/data-0).
[Web Feature services (WFS)](https://www.ogc.org/publications/standard/wfs/) represent a change in the way geographic information is created, modified and exchanged on the Internet and offer direct fine-grained access to geographic information at the feature and feature property level.
Features are representation of geographic entities, such as a coastlines, marine protected areas, offshore platforms, or fishing areas. In WFS, features have geometry (spatial information) and attributes (descriptive data).
emodnet.wfs aims at offering an user-friendly interface to this rich data.

## Installation and setup
Expand All @@ -44,12 +45,23 @@ set the `"emodnet.wfs.quiet"` option to `TRUE`.
options("emodnet.wfs.quiet" = TRUE)
```

## Available services
## Pre-requisites

All available services are contained in the tibble returned by `emodnet_wfs()`.
The emodnet.wfs is designed to be compatible with the modern R geospatial stack, in particular output geospatial objects are [`sf`](https://r-spatial.github.io/sf/) objects, that is to say, a tibble with a geometry list-column.

For users not familiar yet with geospatial data in R, we recommend the following resources:

```{r, echo=FALSE}
- [Spatial Data Science With Applications in R](https://r-spatial.org/book/) by Edzer Pebesma and Roger Bivand.

- [Geocomputation with R](https://r.geocompx.org/) by Robin Lovelace, Jakub Nowosad and Jannes Muenchow.

In the documentation we assume a basic familiarity with spatial data: knowing about coordinates and about projections / [coordinate reference systems (CRS)](https://r.geocompx.org/spatial-class#crs-intro).

## Available data sources (services)

All available data sources, called services, are contained in the [tibble](https://tibble.tidyverse.org/) returned by `emodnet_wfs()`.

```{r, echo=TRUE}
library(emodnet.wfs)
services <- emodnet_wfs()
class(services)
Expand All @@ -59,7 +71,9 @@ services$service_name

To explore available services you can use `View()` or your usual way to explore `data.frames`.

## Create Service Client
## Initialise a WFS Service Client

A WFS service client is responsible for sending requests to a WFS server and processing the responses to retrieve, display, or analyze geospatial features. As such, initialising a client is the first step to interacting with an EMODnet Web Feature Services.

Specify the service using the `service` argument.

Expand All @@ -69,9 +83,11 @@ wfs_bio <- emodnet_init_wfs_client(service = "biology")
wfs_bio
```

## Get WFS Layer info
## List contents of a WFS: Get layer information from a service client

You can get metadata about the layers available from a service.
In the context of a Web Feature Service (WFS), a layer refers to a logical grouping of geographic features that share the same schema (i.e., the same feature type, geometry, and attributes). Layers are the units of data that clients can query, retrieve, and manipulate through a WFS.

You can access information (metadata) about each layer available from an EMODnet WFS with `emodnet_get_wfs_info()`

```{r}
emodnet_get_wfs_info(service = "biology")
Expand Down Expand Up @@ -99,16 +115,20 @@ emodnet_get_all_wfs_info()
```


## Get WFS layers
## Get data from a data source: get layers

You can extract layers directly from a `wfs` object using layer names.
All layers are downloaded as `sf` objects and output as a list with a named element for each layer requested.
The argument `reduce_layers = TRUE` stack all the layers in one single tibble, if possible (for instance if all column names are the same, otherwise it fails).

By default, `emodnet_get_layers()` returns a list of sf objects, one per layer.


```{r}
emodnet_get_layers(wfs = wfs_bio, layers = layers)
```

You can change the output `crs` through the argument `crs`.
You can change the output Coordinate Reference System (CRS), which defines how geographic data is mapped to the Earth's surface, through the argument `crs`.

```{r}
emodnet_get_layers(wfs = wfs_bio, layers = layers, crs = 3857)
Expand Down Expand Up @@ -154,36 +174,44 @@ If you get an unexpected error,
- Look up the [EMODnet monitor](https://monitor.emodnet.eu/resources?lang=en&resource_type=OGC:WFS);
- Open an issue in this [repository](https://github.com/EMODnet/emodnet.wfs/issues).

## Other web services
## Unlock the Full Potential of the EMODnet Web Services: Access Raster and Gridded datasets.

EMODnet hosts a wealth of marine and maritime data distributed through three complementary web services: WFS, WCS, and ERDDAP. Web services allow users to retrieve data programmatically from remote servers, eliminating the need for manual downloads. This is particularly useful for handling large datasets or conducting dynamic analyses. These services are tailored to different data types and research needs, but together, they ensure seamless access to all EMODnet vector, raster, and gridded datasets. Vector data, such as shipwrecks or boundaries, are accessible through `emodnet.wfs` via Web Feature Services (WFS). Complementary, raster and gridded datasets are available through Web Coverage Services (WCS) and ERDDAP respectively.

### Access EMODnet raster data through Web Coverage Services with `EMODnetWCS` in R

EMODnet raster datasets, such as habitat maps or bathymetry, are available through [Web Coverage Services (WCS)](https://wikipedia.org/wiki/Web_Coverage_Service). These data are continuous, gridded, and often used for spatial visualization or environmental modeling. The EMODnetWCS R package provides tools to retrieve and process these raser datasets, in a similar fashion as `emodnet.wfs`. Extensive documentation is available at the [EMODnetWCS website](https://emodnet.github.io/EMODnetWCS/).

There are three ways to access EMODnet data at the moment, that complement each other.

### EMODnet ERDDAP server
### Access EMODnet gridded and tabular datasets through the ERDDAP Server and `rerddap` in R

Some EMODnet data are also published in an [ERDDAP server](https://erddap.emodnet.eu). You can access these data in R using the [rerddap R package](https://docs.ropensci.org/rerddap/):
Both WFS and WCS EMODnet services are based on a federated system: each EMODnet thematic lot manages their servers and data, ensuring that their data are exposed both via WFS and WCS. The twin R packages `emodnet.wfs` and `EMODnetWCS` simplify the access to all the entry points by collecting them in single places, which are the packages themselves.

In contrast, the [EMODnet ERDDAP Server](https://erddap.emodnet.eu) is centrally managed by the EMODnet Central Portal, offering a single access point to all gridded and tabular datasets. ERDDAP simplifies access to datasets such as digital terrain models, vessel density or environmental data. It is particularly suited for large-scale, multidimensional data analysis. In R, the `rerddap` package allows users to query and subset ERDDAP data programmatically, enabling efficient analysis and integration into workflows. For example, researchers can retrieve datasets on vessel density.

```{r rerddap}
# install.packages("rerrdap")
library(rerddap)

# This is the url where the EMODnet ERDDAP server is located
erddap_url <- "https://erddap.emodnet.eu/erddap/"

rerddap::ed_datasets(url = erddap_url)
# Inspect all available datasets
ed_datasets(url = erddap_url)

rerddap::ed_search(query = "vessel density", url = erddap_url)
# Find datasets with the key words "vessel density"
ed_search(query = "vessel density", url = erddap_url)

human_activities_data_info <- rerddap::info(datasetid = "humanactivities_9f8a_3389_f08a", url = erddap_url)
# Inspect more info about the vessel density dataset, using its identifier
human_activities_data_info <- info(datasetid = "humanactivities_9f8a_3389_f08a", url = erddap_url)
human_activities_data_info

# Retrieve the vessel density at a particular time period
year_2020_gridded_data <- griddap(datasetx = human_activities_data_info, time = c("2020-03-18", "2020-03-19"))
head(year_2020_gridded_data$data)
```


### EMODnetWCS: Access EMODnet Web Coverage Service data

This package emodnet.wfs uses [Web Feature Services](https://www.ogc.org/publications/standard/wfs/), hence it is limited to getting vector data. EMODnet also hosts raster data that can be accessed via [Web Coverage Services (WCS)](https://www.ogc.org/publications/standard/wcs/). The R package [EMODnetWCS](https://github.com/EMODnet/EMODnetWCS) makes these data available in R.
More functionalities are available through `rerddap`. Feel free to explore the [rerddap website](https://docs.ropensci.org/rerddap/) to find out what else can you do with the EMODnet datasets in ERDDAP.

## Citation

Expand All @@ -196,3 +224,4 @@ citation(package = "emodnet.wfs")
## Acknowledgements

This package was started by the Sheffield University during the EMODnet Biology WP4 data products workshop in June 2020.

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