Finding data

In rnaturalearth: World Map Data from Natural Earth

library(rnaturalearth)
library(sf)

Available data

There are a lot of data that can be downloaded from Natural Earth with ne_download(). These data are divided into two main categories: physical and cultural vector data. The df_layers_physical and df_layers_cultural data frames included in the rnaturalearth packages show what layer of data can be downloaded.

Physical vector data

data(df_layers_physical)

knitr::kable(
  df_layers_physical,
  caption = "physical vector data available via ne_download()"
)

Table: physical vector data available via ne_download()

|layer | scale10| scale50| scale110| |:----------------------------------|-------:|-------:|--------:| |antarctic_ice_shelves_lines | 1| 1| 0| |antarctic_ice_shelves_polys | 1| 1| 0| |coastline | 1| 1| 1| |geographic_lines | 1| 1| 1| |geography_marine_polys | 1| 1| 1| |geography_regions_elevation_points | 1| 1| 1| |geography_regions_points | 1| 1| 1| |geography_regions_polys | 1| 1| 1| |glaciated_areas | 1| 1| 1| |lakes | 1| 1| 1| |lakes_europe | 1| 0| 0| |lakes_historic | 1| 1| 0| |lakes_north_america | 1| 0| 0| |lakes_pluvial | 1| 0| 0| |land | 1| 1| 1| |land_ocean_label_points | 1| 0| 0| |land_ocean_seams | 1| 0| 0| |land_scale_rank | 1| 0| 0| |minor_islands | 1| 0| 0| |minor_islands_coastline | 1| 0| 0| |minor_islands_label_points | 1| 0| 0| |ocean | 1| 1| 1| |ocean_scale_rank | 1| 0| 0| |playas | 1| 1| 0| |reefs | 1| 0| 0| |rivers_europe | 1| 0| 0| |rivers_lake_centerlines | 1| 1| 1| |rivers_lake_centerlines_scale_rank | 1| 1| 0| |rivers_north_america | 1| 0| 0|

Based on the previous table, we know that we can download the ocean vector at small scale (110). Note that scales are defined as one of 110, 50, 10 or small, medium, large.

plot(
  ne_download(type = "ocean", category = "physical", scale = "small")["geometry"],
  col = "lightblue"
)
#> Reading layer `ne_110m_ocean' from data source 
#>   `/tmp/RtmpapHyoT/ne_110m_ocean.shp' using driver `ESRI Shapefile'
#> Warning in CPL_read_ogr(dsn, layer, query,
#> as.character(options), quiet, : GDAL Message 1:
#> /tmp/RtmpapHyoT/ne_110m_ocean.shp contains polygon(s) with
#> rings with invalid winding order. Autocorrecting them, but
#> that shapefile should be corrected using ogr2ogr for
#> example.
#> Simple feature collection with 2 features and 3 fields
#> Geometry type: POLYGON
#> Dimension:     XY
#> Bounding box:  xmin: -180 ymin: -85.60904 xmax: 180 ymax: 90
#> Geodetic CRS:  WGS 84

Cultural vector data

data(df_layers_cultural)

knitr::kable(
  df_layers_cultural,
  caption = "cultural vector data available via ne_download()"
)

Table: cultural vector data available via ne_download()

|layer | scale10| scale50| scale110| |:-----------------------------------------------|-------:|-------:|--------:| |admin_0_antarctic_claim_limit_lines | 1| 0| 0| |admin_0_antarctic_claims | 1| 0| 0| |admin_0_boundary_lines_disputed_areas | 1| 1| 0| |admin_0_boundary_lines_land | 1| 1| 1| |admin_0_boundary_lines_map_units | 1| 0| 0| |admin_0_boundary_lines_maritime_indicator | 1| 1| 0| |admin_0_boundary_map_units | 0| 1| 0| |admin_0_breakaway_disputed_areas | 0| 1| 0| |admin_0_countries | 1| 1| 1| |admin_0_countries_lakes | 1| 1| 1| |admin_0_disputed_areas | 1| 0| 0| |admin_0_disputed_areas_scale_rank_minor_islands | 1| 0| 0| |admin_0_label_points | 1| 0| 0| |admin_0_map_subunits | 1| 1| 0| |admin_0_map_units | 1| 1| 1| |admin_0_pacific_groupings | 1| 1| 1| |admin_0_scale_rank | 1| 1| 1| |admin_0_scale_rank_minor_islands | 1| 0| 0| |admin_0_seams | 1| 0| 0| |admin_0_sovereignty | 1| 1| 1| |admin_0_tiny_countries | 0| 1| 1| |admin_0_tiny_countries_scale_rank | 0| 1| 0| |admin_1_label_points | 1| 0| 0| |admin_1_seams | 1| 0| 0| |admin_1_states_provinces | 1| 1| 1| |admin_1_states_provinces_lakes | 1| 1| 1| |admin_1_states_provinces_lines | 1| 1| 1| |admin_1_states_provinces_scale_rank | 1| 1| 1| |airports | 1| 1| 0| |parks_and_protected_lands_area | 1| 0| 0| |parks_and_protected_lands_line | 1| 0| 0| |parks_and_protected_lands_point | 1| 0| 0| |parks_and_protected_lands_scale_rank | 1| 0| 0| |populated_places | 1| 1| 1| |populated_places_simple | 1| 1| 1| |ports | 1| 1| 0| |railroads | 1| 0| 0| |railroads_north_america | 1| 0| 0| |roads | 1| 0| 0| |roads_north_america | 1| 0| 0| |time_zones | 1| 0| 0| |urban_areas | 1| 1| 0| |urban_areas_landscan | 1| 0| 0|

plot(
  ne_download(
    type = "airports",
    category = "cultural",
    scale = 10
  )["geometry"],
  pch = 21,
  bg = "grey"
)
#> Reading layer `ne_10m_airports' from data source 
#>   `/tmp/RtmpapHyoT/ne_10m_airports.shp' using driver `ESRI Shapefile'
#> Simple feature collection with 893 features and 40 fields
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: -175.1356 ymin: -53.78147 xmax: 179.1954 ymax: 78.24672
#> Geodetic CRS:  WGS 84

Searching for countries and continents

In this article, we explore how we can search for data available to download within rnaturalearth. Let's begin by loading country data using the read_sf() function from the sf package. In the following code snippet, we read the Natural Earth dataset, which contains information about the sovereignty of countries.

df <- read_sf("/vsizip/vsicurl/https://www.naturalearthdata.com/http//www.naturalearthdata.com/download/10m/cultural/ne_10m_admin_0_sovereignty.zip")

head(df)
#> Simple feature collection with 6 features and 168 fields
#> Geometry type: MULTIPOLYGON
#> Dimension:     XY
#> Bounding box:  xmin: -109.4537 ymin: -55.9185 xmax: 140.9776 ymax: 7.35578
#> Geodetic CRS:  WGS 84
#> # A tibble: 6 × 169
#>   featurecla   scalerank LABELRANK SOVEREIGNT SOV_A3 ADM0_DIF
#>   <chr>            <int>     <int> <chr>      <chr>     <int>
#> 1 Admin-0 sov…         5         2 Indonesia  IDN           0
#> 2 Admin-0 sov…         5         3 Malaysia   MYS           0
#> 3 Admin-0 sov…         0         2 Chile      CHL           0
#> 4 Admin-0 sov…         0         3 Bolivia    BOL           0
#> 5 Admin-0 sov…         0         2 Peru       PER           0
#> 6 Admin-0 sov…         0         2 Argentina  ARG           0
#> # ℹ 163 more variables: LEVEL <int>, TYPE <chr>, TLC <chr>,
#> #   ADMIN <chr>, ADM0_A3 <chr>, GEOU_DIF <int>,
#> #   GEOUNIT <chr>, GU_A3 <chr>, SU_DIF <int>, SUBUNIT <chr>,
#> #   SU_A3 <chr>, BRK_DIFF <int>, NAME <chr>,
#> #   NAME_LONG <chr>, BRK_A3 <chr>, BRK_NAME <chr>,
#> #   BRK_GROUP <chr>, ABBREV <chr>, POSTAL <chr>,
#> #   FORMAL_EN <chr>, FORMAL_FR <chr>, NAME_CIAWF <chr>, …

Finding countries

One way to search for countries is to search within the ADMIN vector. Let's start by plotting some of the first countries.

lapply(df$ADMIN[1:6], \(x) {
  plot(ne_countries(country = x)["geometry"], main = x)
})

Suppose that we want to search the polygons for the US, how should we spell it?

ne_countries(country = "USA")
ne_countries(country = "United States")
ne_countries(country = "United States Of America")
ne_countries(country = "United States of America")

One possibility consists to search within the ADMIN vector using a regular expression to find all occurrences of the word states.

df$ADMIN[grepl("states", df$ADMIN, ignore.case = TRUE)]
#> [1] "United States of America"      
#> [2] "Federated States of Micronesia"

We can now get the data.

plot(ne_countries(country = "United States of America")["geometry"])

Continents

Finally, let's create plots for each continent using the ne_countries function with the continent parameter.

unique(df$CONTINENT)
#> [1] "Asia"                    "South America"          
#> [3] "Europe"                  "Africa"                 
#> [5] "North America"           "Oceania"                
#> [7] "Antarctica"              "Seven seas (open ocean)"

lapply(unique(df$CONTINENT), \(x) {
  plot(
    ne_countries(
      continent = x,
      scale = "medium"
    )["geometry"],
    main = x
  )
})

rnaturalearth documentation built on May 29, 2024, 7:31 a.m.