Belgium

BelgiumMaps.StatBel by Jan Wijfels (bnosac): convenient R package bundeling spatial open data on Belgian administrative boundaries.

Load package (library(BelgiumMaps.StatBel)) and then use data() to load the spatial data for the administrative level you need:

• BE_ADMIN_SECTORS: statistical sector / statistische sector
• BE_ADMIN_MUNTY: municipality / gemeente
• BE_ADMIN_DISTRICT: district / arrondissement
• BE_ADMIN_PROVINCE: province / provincie
• BE_ADMIN_REGION: region / regio
• BE_ADMIN_BELGIUM: country / land

Important: the data always contains a variable/column with the NIS-code, named “CD_[level]_REFNIS“. E.g. CD_PROV_REFNIS, CD_RGN_REFNIS, CD_MUNTY_REFNIS. With NIS-codes in your data, you can merge on each level. It also contains NUTS-codes (not demonstrated).

library(BelgiumMaps.StatBel)
data("BE_ADMIN_PROVINCE") # load spatial object for provincial level
provinces <- st_as_sf(BE_ADMIN_PROVINCE) # convert to sf-object

qtm(provinces) # plot with tmap

data("BE_ADMIN_MUNTY")
munip <- st_as_sf(BE_ADMIN_MUNTY)
qtm(munip)

Europe

The eurostat package allows you to directly download, analyse and visualise data from Eurostat in R, including their blank maps of EU-member countries:

• Use the function get_eurostat_geospatial() to download.
• Choose the NUTS level: “0” (countries), “1” (regions, i.e. Flanders), “2” (sub-region, BE: provinces), “3” (sub-sub-region, BE: arrondissment).
• Choose the level of detail: “60” (1:60million), “20” (1:20million), “10” (1:10million), “01” (1:1million). More detail for more zoomed-in maps (longer download, but cached).
• Identifier: NUTS (“NUTS_ID”).
• sf-object by default, no st_as_sf() needed.
• Warning: not EU-member (+ NO, TR, etc.), not on the map!

library(eurostat)
eu_nuts0 <- get_eurostat_geospatial(
  resolution = "60", # detail 
  nuts_level = "0") # NUTS 0-3

eu_nuts2 <- get_eurostat_geospatial(
  resolution = "60", # detail 
  nuts_level = "2") # NUTS 0-3

qtm(eu_nuts0)

qtm(eu_nuts2)

World

Various R packages containing spatial data for the entire world, e.g.:

• tmap: load using `data(“World”).
• rworldmap (regular resolution) and complementary package rworldxtra (high resolution)

library(tmap)
data("World")
world_tmap <- st_as_sf(World)
qtm(world_tmap)

library(rworldmap)
#library(rworldxtra)

# load worldmap with resolution "coarse", "low", "less islands", "li", "high".
# for option "high" the additional package rworldxtra needs to be install, works the same.
world_worldmap <- getMap(resolution = "low")
world_worldmap <- st_as_sf(world_worldmap)

qtm(world_worldmap)

Filter or select

Use a variable (originally in spatial dataset or added by you) to filter/select what you want from a larger map.

data("BE_ADMIN_PROVINCE")
prov <- st_as_sf(BE_ADMIN_PROVINCE)

qtm(prov)

# filter out only the provinces in the region of Flanders, i.e. 
# where the region description variable "TX_RGN_DESCR_NL" is equal to "Vlaams Gewest"
prov.fl <- prov %>%
  filter(TX_RGN_DESCR_NL == 'Vlaams Gewest')

qtm(prov.fl)

# filter out the South American countries from the world map
south_am <- world_worldmap %>% 
  filter(GEO3 == 'South America')

qtm(south_am)

Limit visible area

Happens “at the end” when displaying the map, so depedent on what you use to display/plot. Example with tmap and ggplot:

qtm(eu_nuts2, bbox = 'France')

ggplot(eu_nuts0) +
  geom_sf() +
  coord_sf(
    # limit map to 'mainland' EU
    xlim = c(2500000, 6000000), ylim =c(1500000, 5300000),
    crs = 3035)

Crop spatial features

Use st_crop() from the sf package to crop a map to certain limits (remove rest)

eu <- st_crop(eu_nuts0, c(xmin=-10, xmax=45, ymin=36, ymax=71))
qtm(eu)

Combine filter, crop, limit

# Filter out the Benelux based on country-names 
benelux <- world_worldmap %>%
  filter(NAME %in% c('Belgium', 'Netherlands', 'Luxembourg'))

# Plot Benelux and (exactly) limit map (decolonisation)
ggplot(benelux) +
  geom_sf() +
  coord_sf(xlim = c(3700000, 4300000),
           ylim =c(2800000, 3500000), crs = 3035)