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README.Rmd
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README.Rmd
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---
title: "mapinsetr"
author: Timothee Giraud
output:
md_document:
variant: gfm
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
```{r knitr_init, echo=FALSE, cache=FALSE}
library(knitr)
## Global options
options(max.print="75")
opts_chunk$set(echo=TRUE,
cache=FALSE,
prompt=FALSE,
tidy=TRUE,
comment=NA,
message=FALSE,
warning=FALSE,
fig.width=7)
opts_knit$set(width=75)
knit_hooks$set(par = function(before, options, envir){
if (before){
par(mar=c(0,0,0,0))
}
})
knit_hooks$set(par.title = function(before, options, envir){
if (before){
par(mar=c(0,0,1.2,0))
}
})
```
# Create Map Insets with `mapinsetr`
<!-- badges: start -->
[](https://github.com/riatelab/mapinsetr/actions/workflows/R-CMD-check.yaml)
<!-- badges: end -->
Map insets are small zoom-in or zoom-out maps that focus on particular territories within a general map. `mapinsetr` provides a set of functions that helps to create such insets.
## Installation
```{r, eval=FALSE}
require(devtools)
devtools::install_github("riatelab/mapinsetr")
```
## Version
The [previous version](https://github.com/riatelab/mapinsetr/releases/tag/v0.1.0) of the package was based on `sp`, `rgeos` and `maptools`.
This version (0.2.0) is based on the [`sf` package](https://github.com/r-spatial/sf) only.
## Example
The aim of this example is to create a base map of Algeria's municipalities with an inset on the Algiers wilaya.
Here are the few steps of the base map creation process:
- download data on Algerian administrative boundaries,
- create a mask that will help to extract the municipalities,
- create an inset of Alger municipalities within the previously created mask,
- merge the original basemap and inset
### Download data on Algerian administrative boundaries.
The `raster` package offers an access to the [GADM database](http://www.gadm.org/) through the `getData()` function.
The ISO3 code of Algeria is **DZA** and we will need 2 levels of administrative data (**0** for the state and **2** for the municipalities).
Basemaps (`SpatialPolygonsDataFrame`) are downloaded unprojected in WGS84. We have to transform them into simple feature collections (`sf` objects) and project them in a valid projection (the EPSG code 30791 stands for "Nord Sahara 1959 / Voirol Unifie Nord").
```{r dowload, par=TRUE}
library(raster)
library(sf)
# download data from gadm.org
adm0 <-st_as_sf( getData(name = "GADM", country = "DZA", level = 0, path = tempdir() ))
adm0 <- st_transform(adm0, 30791)
adm2 <- st_as_sf(getData(name = "GADM", country = "DZA", level = 2, path = tempdir()))
adm2 <- st_transform(adm2, 30791)
# plot
plot(st_geometry(adm0), lwd = 2)
plot(st_geometry(adm2), add = T, col = "grey80", lwd = 0.2)
```
### Create a mask that will help to extract the municipalities
Our goal is to extract Alger municipalities. To extract those munuicipalities we will use a mask.
This mask has to be an sf object. The `create_mask` function create a mask based on a bbox, a sf or sfc extent or an interactively defined rectangle.
In this example we use a mask defined by Alger willaya extent + a 2 km buffer.
```{r mask, par = TRUE}
library(mapinsetr)
alger_extent <- st_buffer(adm2[adm2$NAME_1=="Alger", ],dist = 2000)
box_alger <- create_mask(bb = alger_extent)
plot(st_geometry(adm0), lwd = 2)
plot(st_geometry(adm2), add=T, col = "grey80", lwd = 0.2)
plot(st_geometry(box_alger), border = "red", add=T, lwd = 2)
```
Alternatively, one can define the mask interactively on the plot :
```{r mask2, eval=FALSE}
library(mapinsetr)
plot(st_geometry(adm0), lwd = 2)
plot(st_geometry(adm2), add=T, col = "grey80", lwd = 0.2)
box_alger_interactive <- create_mask(interactive = TRUE, add=TRUE,
prj = st_crs(adm0))
```
### Create an inset of Alger municipalities within the previously created mask
The `move_and_resize` function extracts polygons or multipolygons (`x`) within a mask (`mask`), moves them to coordinates (`xy`, bottom left corner of the inset) and resizes them according to a factor (`k`).
```{r createInset, par = TRUE}
zoom_alger <- move_and_resize(x = adm2, mask = box_alger, xy = c(-1000000, -100000), k = 15)
box <- move_and_resize(x = box_alger, mask = box_alger, xy = c(-1000000, -100000), k = 15)
plot(st_geometry(adm0), lwd = 2)
plot(st_geometry(adm2), add=T, col = "grey80", lwd = 0.2)
plot(st_geometry(box_alger), border = "red", add=T, lwd = 2)
plot(st_geometry(zoom_alger), add=T, col = "grey80", lwd = 0.2)
plot(st_geometry(box), border = "red", lwd = 1, add=T)
```
### Merge the original basemap and inset
We currently have 2 sf objects, the next step is to merge them in a single one
`inset_rbinder` merge the initial basemap and the inset.
```{r mergespdf, par.title = TRUE}
adm2final <- inset_rbinder(list(adm2, zoom_alger))
plot(st_geometry(adm2final), col = "grey80", lwd = 0.2)
title("Final basemap with inset!")
```
### Plot an example
The following example build a map of Municipalities types.
```{r ex, par.title = TRUE}
library(cartography)
adm2final[adm2final$CCA_2==2223, "TYPE_2"] <- "Commune"
plot(st_geometry(adm0), lwd = 2)
typoLayer(adm2final, var = "TYPE_2",
legend.title.txt = "Commune Type",
border = "white", lwd = 0.1,
col = carto.pal("multi.pal", 3),
legend.pos = "topright", add = T)
plot(st_geometry(box_alger), border = "red", add=T, lwd = 2)
plot(st_geometry(box), border = "red", lwd = 2, add=T)
layoutLayer(title = "Commune Types in Algeria with a Zoom on Alger Region",
sources = "GADM 2.8, 2015", author = "@rCarto", theme = "green.pal")
```