mapview.Rmd

---
title: "mapview"
author: "Jamie Montgomery"
date: "2/4/2020"
output: html_document
---

# Overview

This is a basic introduction to the `mapview` packaged developed by Tim Appelhans and others. For more information on the package and even more tutorials check out [https://r-spatial.github.io/mapview/index.html](https://r-spatial.github.io/mapview/index.html)


## Setup

You will need the `sf`, `mapview` and `raster` packages. 

```{r setup, warning = F, message = F}
knitr::opts_chunk$set(echo = TRUE, warning = F, message = F)

library(sf)
library(mapview)
library(raster)
```

## Load spatial data

### Point data

The `sb-tweets` shapefile is a spatial dataframe of tweets from Santa Barbara  between September & November of 2019.

```{r load_tweets}
sb_tweets <- read_sf("data/sb-tweets.shp")
```

Time for `mapview`

```{r mapview}
mapview(sb_tweets)
```

Play with color

```{r}
mapview(sb_tweets, zcol = "usr_typ")
```

```{r}
mapview(sb_tweets, zcol = "Month")
```

Playing with continuous (using days here which isn't usually what you would do)

```{r}
mapview(sb_tweets, zcol = "Day")
```

### Polygon data

The California Protected Areas Database (CPAD) can be downloaded at: [https://www.calands.org/](https://www.calands.org/). I've already cropped it to the Santa Barbara area, and selected just a few of the columns, but the full dataset covers the entire state and has a lot more information.

```{r load_cpad}
#read in data
cpad <- read_sf("data/ca_protected_areas.shp")

#simple view
mapview(cpad)
```

You can play with color using the `zcol` argument to set the variable to color by. In this case we will use Access Type.

```{r color_by_variable}
mapview(cpad, zcol = "ACCESS_TYP")
```

By adding `burst = TRUE` to the `mapview` function you can split out a variable into unique layers according to all unique values of the variable

```{r burst}
mapview(cpad, zcol = "ACCESS_TYP", burst = TRUE)
```


You can set your own color palette or even discrete colors using the `col.regions` argument.

```{r set_colors}
mapview(cpad, zcol = "ACCESS_TYP", col.regions = c("purple", "yellow", "darkgreen", "orange"))
mapview(cpad, zcol = "ACCESS_TYP", col.regions = mapviewPalette("mapviewSpectralColors")) 
```

Easily combine layers using the `+`, and set label titles.

```{r combine_layers}
mapview(cpad, zcol = "ACCESS_TYP", layer.name = "CPAD Access") + 
  mapview(sb_tweets, zcol = "usr_typ", layer.name = "SB Tweets", col.regions = c("darkgreen", "darkblue"))

```

You can change the basemap and also turn on and off layers that you've added to the map using the controls on the left hand side of the map.

### Raster

You can also plot raster data. The data here is fish catch in tons/km2 for the US Northeast region from 2015. It's a big raster but mapview scales it for viewing.  As you hover over the cells you see the value pop up on the top right portion of the map.

```{r raster}
catch <- raster("data/catch_2015.tif") 

mapview(catch)
```


## Save with `mapshot`

You can use the `mapshot` argument to save a map either as an interactive .html to share with others or post online, or a static png. When I first tried this I got a PhantomJS error:

> `PhantomJS not found. You can install it with webshot::install_phantomjs(). If it is installed, please make sure the phantomjs executable can be found via the PATH variable.`

and had to install it before it worked...

```{r save}
#first name the map

map <- mapview(sb_tweets, zcol = "usr_typ")

mapshot(map, file = "sb_tweet_map.png")
```