The package sp(E. J. Pebesma and Bivand 2005) provides class and methods for vector spatial data in R. It allows displaying background maps, inspectiong an attribute table etc.
The package rgeos(Bivand and Rundel 2021) gives access to the GEOS spatial operations library and therefore makes classic GIS operations available: calculation of surfaces or perimeters, calculation of distances, spatial aggregations, buffer zones, intersections, etc.
The package raster(Hijmans 2022a) is dedicated to the import, manipulation and modeling of raster data.
Today, the main developments concerning vector data have moved away from the old 3 (sp, rgdal, rgeos) to rely mainly on the package sf ((E. Pebesma 2018a), (E. Pebesma 2018b)). In this manual we will rely exclusively on this package to manipulate vector data.
The packages stars(E. Pebesma 2021) and terra(Hijmans 2022b) come to replace the package raster for processing raster data. We have chosen to use the package here terra for its proximity to the raster.
1.2 The package sf
The package sf was released in late 2016 by Edzer Pebesma (also author of sp). Its goal is to combine the feature of sp, rgeos and rgdal in a single, more ergonomic package. This package offers simple objects (following the simple feature standard) which are easier to manipulate. Particular attention has been paid to the compatibility of the package with the pipe syntax and the operators of the tidyverse.
sf directly uses the GDAL, GEOS and PROJ libraries.
Many of the spatial data available on the internet are in shapefile format, which can be opened in the following way
library(sf)
Linking to GEOS 3.10.2, GDAL 3.4.3, PROJ 8.2.1; sf_use_s2() is TRUE
district <-st_read("data_cambodia/district.shp")
Reading layer `district' from data source
`/home/lucas/Documents/ForgeIRD/rspatial-for-onehealth/data_cambodia/district.shp'
using driver `ESRI Shapefile'
Simple feature collection with 197 features and 10 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 211534.7 ymin: 1149105 xmax: 784612.1 ymax: 1625495
Projected CRS: WGS 84 / UTM zone 48N
Shapefile format limitations
For the multiple limitations of this format (multi-file, limited number of records…) we advise you to prefer another format such as the geopackage *.gpkg. All the good reasons not to use the shapefile are here.
A geopackage is a database, to load a layer, you must know its name
st_layers("data_cambodia/cambodia.gpkg")
Driver: GPKG
Available layers:
layer_name geometry_type features fields crs_name
1 country Multi Polygon 1 10 WGS 84 / UTM zone 48N
2 district Multi Polygon 197 10 WGS 84 / UTM zone 48N
3 education Multi Polygon 25 19 WGS 84 / UTM zone 48N
4 hospital Point 956 13 WGS 84 / UTM zone 48N
5 cases Multi Point 972 2 WGS 84 / UTM zone 48N
6 road Multi Line String 6 9 WGS 84 / UTM zone 48N
Reading layer `road' from data source
`/home/lucas/Documents/ForgeIRD/rspatial-for-onehealth/data_cambodia/cambodia.gpkg'
using driver `GPKG'
Simple feature collection with 6 features and 9 fields
Geometry type: MULTILINESTRING
Dimension: XY
Bounding box: xmin: 212377 ymin: 1152214 xmax: 784654.7 ymax: 1625281
Projected CRS: WGS 84 / UTM zone 48N
1.2.1 Format of spatial objects sf
Objectssf are objects in data.frame which one of the columns contains geometries. This column is the class of sfc (simple feature column) and each individual of the column is a sfg (simple feature geometry). This format is very practical insofa as the data and the geometries are intrinsically linked in the same object.
A benchmark of vector processing libraries is available here.
1.3 Package mapsf
The free R software spatial ecosystem is rich, dynamic and mature and several packages allow to import, process and represent spatial data. The package mapsf(Giraud 2022) relies on this ecosystem to integrate the creation of quality thematic maps into processing chains with R.
Other packages can be used to make thematic maps. The package ggplot2(Wickham 2016), in association with the package ggspatial(Dunnington 2021), allows for example to display spatial objects and to make simple thematic maps. The package tmap(Tennekes 2018) is dedicated to the creation of thematic maps, it uses a syntax close to that of ggplot2 (sequence of instructions combined with the ‘+’ sign). Documentation and tutorials for using these two packages are readily available on the web.
Here, we will mainly use the package mapsf whose functionalities are quite complete and the handling rather simple. In addition, the package is relatively light.
mapsf allows you to create most of the types of map usually used in statistical cartography (choropleth maps, typologies, proportional or graduated symbols, etc.). For each type of map, several parameters are used to customize the cartographic representation. These parameters are the same as those found in the usual GIS or cartography software (for example, the choice of discretizations and color palettes, the modification of the size of the symbols or the customization of the legends). Associated with the data representation functions, other functions are dedicated to cartographic dressing (themes or graphic charters, legends, scales, orientation arrows, title, credits, annotations, etc.), the creation of boxes or the exporting maps. mapsf is the successor of cartography(Giraud and Lambert 2016), it offers the same main functionalities while being lighter and more ergonomic.
To use this package several sources can be consulted:
The package documentation accessible on the internet or directly in R (?mapsf),
The vignettes associated with the package show sample scripts,
The R Geomatics blog which provides resources and examples related to the package and more generally to the R spatial ecosystem.
1.4 The package terra
The package terra was release in early 2020 by Robert J. Hijmans (also author of raster). Its objective is to propose methods of treatment and analysis of raster data. This package is very similar to the package raster; but it has more features, it’s easier to use, and it’s faster.
The package 
The package