8.2 Geographic Data Packages

Many R packages provide convenient interfaces to spatial libraries or geoportals

Package	Description
`osmdata`	small OpenStreetMap datasets.
`osmextract`	large OpenStreetMap datasets.
`geodata`	Download and import imports administrative, elevation, WorldClim data.
`rnaturalearth`	ropensci Natural Earth
`rnoaa`	(NOAA) climate data
`tidycensus`	US Demographics
`tigris`	US maps
`cancensus`	Canada Demographics
`eurostat`	EU
`giscoR`	EU
`idbr`	International Databases
`bcdata`	Province of British Columbia
`geobr`	Brazil
`RCzechia`	Czechia
`GSODR`	Global Summary Weather Data

Each data package has its own syntax for accessing data. See the package vignettes, and in many cases, textbooks.

8.2.1 Example 1: `rnaturalearth`

This package recently changed maintainers and must be updated for dependencies:

library(rnaturalearth)
usa <- ne_countries(country = "United States of America") # United States borders
class(usa)


[1] "SpatialPolygonsDataFrame"
attr(,"package")
[1] "sp"

By default rnaturalearth returns objects of class Spatial*. The result can be converted into an sf objects with st_as_sf().

8.2.2 Example 2: `geodata`

downloads a series of rasters containing global monthly precipitation sums with spatial resolution of ten minutes (~18.5km at the equator)

library(geodata)
worldclim_prec <- worldclim_global("prec", res = 10, path = tempdir())
class(worldclim_prec)


[1] "SpatRaster"
attr(,"package")
[1] "terra"

8.2.3 Example 3: `osmdata`

OpenStreetMap is a vast global database of crowd-sourced data

library(osmdata)
parks <- opq(bbox = "chicago il") |> 
  add_osm_feature(key = "leisure", value = "park") |> 
  osmdata_sf()

A limitation with the osmdata package is that it is rate limited. Use osmextract to cache .pbf files.

The data source and wider OSM ecosystems have many advantages:

they provide datasets that are available globally, free of charge, and constantly improving thanks to an army of volunteers.

Using OSM encourages ‘citizen science’ and contributions back to the digital commons

8.2.4 Built-in datasets

these four methods make the world data shapefile available

library(spData)  # loads all spData datasets
data(world, package = "spData")
world2 = spData::world # retrieves world from spData
world3 = read_sf(system.file("shapes/world.gpkg", package = "spData")) # retrieves world from spData

8.2.5 Geocoding

Another way to obtain spatial information is to transform a description of a location, usually an address, into its coordinates.

Send a query to an online service and getting the location as a result.

Recommends tidygeocoder for the variety of services available with a consistent interface.

Also allows performing the opposite process,reverse geocoding to get a set of information (name, address, etc.) based on coordinates.