{"ok": true, "database": "tils", "table": "til", "rows": [{"path": "gis_natural-earth-in-spatialite-and-datasette.md", "topic": "gis", "title": "Natural Earth in SpatiaLite and Datasette", "url": "https://github.com/simonw/til/blob/main/gis/natural-earth-in-spatialite-and-datasette.md", "body": "Natural Earth ([website](https://www.naturalearthdata.com/), [Wikipedia](https://en.wikipedia.org/wiki/Natural_Earth)) is a a public domain map dataset.\n\nIt's distributed in a bunch of different formats - one of them is a SQLite database file.\n\nhttp://naciscdn.org/naturalearth/packages/natural_earth_vector.sqlite.zip - this is a 423MB file which decompresses to provide a 791MB `packages/natural_earth_vector.sqlite` file.\n\nI opened it in Datasette like this:\n\n    datasette --load-extension spatialite \\\n      ~/Downloads/natural_earth_vector.sqlite/packages/natural_earth_vector.sqlite\n\nI had previously installed Datasette and SpatiaLite using Homebrew:\n\n    brew install datasette spatialite-tools\n\n## Database format\n\nThe database contains 181 tables, for different layers at different scales. Those tables are listed below.\n\nEach table has a bunch of columns and a `GEOMETRY` column. That geometry column contains data stored in WKB - Well-Known Binary format.\n\nIf you have SpatiaLite you can convert that column to GeoJSON like so:\n\n    AsGeoJSON(GeomFromWKB(GEOMETRY))\n\nFor example, here are the largest \"urban areas\" at 50m scale:\n\n```sql\nselect\n  AsGeoJSON(GeomFromWKB(GEOMETRY))\nfrom\n  ne_50m_urban_areas\norder by area_sqkm desc\n```\nEvery country at 50m scale (a good balance between detail and overall size):\n```sql\nselect\n  AsGeoJSON(GeomFromWKB(GEOMETRY)), *\nfrom\n  ne_50m_admin_0_countries\n```\n\nThis query draws a coloured map of countries using the `datasette-geojson-map` and `sqlite-colorbrewer` plugins:\n\n```sql\nselect\n  ogc_fid,\n  GeomFromWKB(GEOMETRY) as geometry,\n  colorbrewer('Paired', 9, MAPCOLOR9 - 1) as fill\nfrom\n  ne_10m_admin_0_countries\n```\n\n<img width=\"1098\" alt=\"Screenshot of a map showing different countries in random colours\" src=\"https://user-images.githubusercontent.com/9599/156858327-08f99300-29fd-4ca8-a268-f8c2ec659349.png\">\n\nThe `ne_10m_admin_1_states_provinces` table is useful: it has subdivisions for a bunch of different countries. Here's the UK divided into counties:\n\n```sql\nselect\n  ogc_fid,\n  GeomFromWKB(GEOMETRY) as geometry,\n  featurecla,\n  scalerank,\n  adm1_code,\n  diss_me,\n  iso_3166_2,\n  wikipedia,\n  iso_a2,\n  adm0_sr,\n  name,\n  name_alt,\n  type,\n  type_en,\n  area_sqkm,\n  latitude,\n  longitude,\n  admin\nfrom\n  ne_10m_admin_1_states_provinces\nwhere\n  admin = 'United Kingdom'\n```\nI tried this with `select *, GeomFromWKB(GEOMETRY) as geometry` first but it didn't work with `datasette-geojson-map` because the `*` picked up the original `GEOMETRY` column in the wrong format.\n\nThe scales are:\n\n- Large scale data, 1:10m - most detailed\n- Medium scale data, 1:50m\n- Small scale data, 1:110m - least detailed\n\n## Exploring with Datasette plugins\n\nWith the `datasette-leaflet-geojson` plugin installed, any column that returns GeoJSON (from `AsGeoJSON(GeomFromWKB(GEOMETRY))`) will render as a little map, no matter what the column name.\n\nIf you install `datasette-geojson-map` you can seee a single map with all of the shapes on - you need to create a `geometry` column containing a SpatiaLite geometry, which you can do like this:\n```sql\nselect\n  ogc_fid, GeomFromWKB(GEOMETRY) as geometry, *\nfrom\n  ne_50m_coastline\n```\n## Full list of tables\n\n- `ne_10m_admin_0_antarctic_claim_limit_lines`\n- `ne_10m_admin_0_antarctic_claims`\n- `ne_10m_admin_0_boundary_lines_disputed_areas`\n- `ne_10m_admin_0_boundary_lines_land`\n- `ne_10m_admin_0_boundary_lines_map_units`\n- `ne_10m_admin_0_boundary_lines_maritime_indicator`\n- `ne_10m_admin_0_boundary_lines_maritime_indicator_chn`\n- `ne_10m_admin_0_countries`\n- `ne_10m_admin_0_countries_arg`\n- `ne_10m_admin_0_countries_bdg`\n- `ne_10m_admin_0_countries_bra`\n- `ne_10m_admin_0_countries_chn`\n- `ne_10m_admin_0_countries_deu`\n- `ne_10m_admin_0_countries_egy`\n- `ne_10m_admin_0_countries_esp`\n- `ne_10m_admin_0_countries_fra`\n- `ne_10m_admin_0_countries_gbr`\n- `ne_10m_admin_0_countries_grc`\n- `ne_10m_admin_0_countries_idn`\n- `ne_10m_admin_0_countries_ind`\n- `ne_10m_admin_0_countries_isr`\n- `ne_10m_admin_0_countries_ita`\n- `ne_10m_admin_0_countries_jpn`\n- `ne_10m_admin_0_countries_kor`\n- `ne_10m_admin_0_countries_lakes`\n- `ne_10m_admin_0_countries_mar`\n- `ne_10m_admin_0_countries_nep`\n- `ne_10m_admin_0_countries_nld`\n- `ne_10m_admin_0_countries_pak`\n- `ne_10m_admin_0_countries_pol`\n- `ne_10m_admin_0_countries_prt`\n- `ne_10m_admin_0_countries_pse`\n- `ne_10m_admin_0_countries_rus`\n- `ne_10m_admin_0_countries_sau`\n- `ne_10m_admin_0_countries_swe`\n- `ne_10m_admin_0_countries_tur`\n- `ne_10m_admin_0_countries_twn`\n- `ne_10m_admin_0_countries_ukr`\n- `ne_10m_admin_0_countries_usa`\n- `ne_10m_admin_0_countries_vnm`\n- `ne_10m_admin_0_disputed_areas`\n- `ne_10m_admin_0_disputed_areas_scale_rank_minor_islands`\n- `ne_10m_admin_0_label_points`\n- `ne_10m_admin_0_map_subunits`\n- `ne_10m_admin_0_map_units`\n- `ne_10m_admin_0_names`\n- `ne_10m_admin_0_pacific_groupings`\n- `ne_10m_admin_0_scale_rank`\n- `ne_10m_admin_0_scale_rank_minor_islands`\n- `ne_10m_admin_0_seams`\n- `ne_10m_admin_0_sovereignty`\n- `ne_10m_admin_1_label_points`\n- `ne_10m_admin_1_label_points_details`\n- `ne_10m_admin_1_seams`\n- `ne_10m_admin_1_sel`\n- `ne_10m_admin_1_states_provinces`\n- `ne_10m_admin_1_states_provinces_lakes`\n- `ne_10m_admin_1_states_provinces_lines`\n- `ne_10m_admin_1_states_provinces_scale_rank`\n- `ne_10m_admin_1_states_provinces_scale_rank_minor_islands`\n- `ne_10m_admin_2_counties`\n- `ne_10m_admin_2_counties_lakes`\n- `ne_10m_admin_2_counties_lines`\n- `ne_10m_admin_2_counties_scale_rank`\n- `ne_10m_admin_2_counties_scale_rank_minor_islands`\n- `ne_10m_admin_2_counties_to_match`\n- `ne_10m_admin_2_label_points`\n- `ne_10m_admin_2_label_points_details`\n- `ne_10m_airports`\n- `ne_10m_antarctic_ice_shelves_lines`\n- `ne_10m_antarctic_ice_shelves_polys`\n- `ne_10m_coastline`\n- `ne_10m_geographic_lines`\n- `ne_10m_geography_marine_polys`\n- `ne_10m_geography_regions_elevation_points`\n- `ne_10m_geography_regions_points`\n- `ne_10m_geography_regions_polys`\n- `ne_10m_glaciated_areas`\n- `ne_10m_lakes`\n- `ne_10m_lakes_australia`\n- `ne_10m_lakes_europe`\n- `ne_10m_lakes_historic`\n- `ne_10m_lakes_north_america`\n- `ne_10m_lakes_pluvial`\n- `ne_10m_land`\n- `ne_10m_land_ocean_label_points`\n- `ne_10m_land_ocean_seams`\n- `ne_10m_land_scale_rank`\n- `ne_10m_minor_islands`\n- `ne_10m_minor_islands_coastline`\n- `ne_10m_minor_islands_label_points`\n- `ne_10m_ocean`\n- `ne_10m_ocean_scale_rank`\n- `ne_10m_parks_and_protected_lands_area`\n- `ne_10m_parks_and_protected_lands_line`\n- `ne_10m_parks_and_protected_lands_point`\n- `ne_10m_parks_and_protected_lands_scale_rank`\n- `ne_10m_playas`\n- `ne_10m_populated_places`\n- `ne_10m_populated_places_simple`\n- `ne_10m_ports`\n- `ne_10m_railroads`\n- `ne_10m_railroads_north_america`\n- `ne_10m_reefs`\n- `ne_10m_rivers_australia`\n- `ne_10m_rivers_europe`\n- `ne_10m_rivers_lake_centerlines`\n- `ne_10m_rivers_lake_centerlines_scale_rank`\n- `ne_10m_rivers_north_america`\n- `ne_10m_roads`\n- `ne_10m_roads_north_america`\n- `ne_10m_time_zones`\n- `ne_10m_urban_areas`\n- `ne_10m_urban_areas_landscan`\n- `ne_110m_admin_0_boundary_lines_land`\n- `ne_110m_admin_0_countries`\n- `ne_110m_admin_0_countries_lakes`\n- `ne_110m_admin_0_map_units`\n- `ne_110m_admin_0_pacific_groupings`\n- `ne_110m_admin_0_scale_rank`\n- `ne_110m_admin_0_sovereignty`\n- `ne_110m_admin_0_tiny_countries`\n- `ne_110m_admin_1_states_provinces`\n- `ne_110m_admin_1_states_provinces_lakes`\n- `ne_110m_admin_1_states_provinces_lines`\n- `ne_110m_admin_1_states_provinces_scale_rank`\n- `ne_110m_coastline`\n- `ne_110m_geographic_lines`\n- `ne_110m_geography_marine_polys`\n- `ne_110m_geography_regions_elevation_points`\n- `ne_110m_geography_regions_points`\n- `ne_110m_geography_regions_polys`\n- `ne_110m_glaciated_areas`\n- `ne_110m_lakes`\n- `ne_110m_land`\n- `ne_110m_ocean`\n- `ne_110m_populated_places`\n- `ne_110m_populated_places_simple`\n- `ne_110m_rivers_lake_centerlines`\n- `ne_50m_admin_0_boundary_lines_disputed_areas`\n- `ne_50m_admin_0_boundary_lines_land`\n- `ne_50m_admin_0_boundary_lines_maritime_indicator`\n- `ne_50m_admin_0_boundary_lines_maritime_indicator_chn`\n- `ne_50m_admin_0_boundary_map_units`\n- `ne_50m_admin_0_breakaway_disputed_areas`\n- `ne_50m_admin_0_breakaway_disputed_areas_scale_rank`\n- `ne_50m_admin_0_countries`\n- `ne_50m_admin_0_countries_lakes`\n- `ne_50m_admin_0_map_subunits`\n- `ne_50m_admin_0_map_units`\n- `ne_50m_admin_0_pacific_groupings`\n- `ne_50m_admin_0_scale_rank`\n- `ne_50m_admin_0_sovereignty`\n- `ne_50m_admin_0_tiny_countries`\n- `ne_50m_admin_0_tiny_countries_scale_rank`\n- `ne_50m_admin_1_seams`\n- `ne_50m_admin_1_states_provinces`\n- `ne_50m_admin_1_states_provinces_lakes`\n- `ne_50m_admin_1_states_provinces_lines`\n- `ne_50m_admin_1_states_provinces_scale_rank`\n- `ne_50m_airports`\n- `ne_50m_antarctic_ice_shelves_lines`\n- `ne_50m_antarctic_ice_shelves_polys`\n- `ne_50m_coastline`\n- `ne_50m_geographic_lines`\n- `ne_50m_geography_marine_polys`\n- `ne_50m_geography_regions_elevation_points`\n- `ne_50m_geography_regions_points`\n- `ne_50m_geography_regions_polys`\n- `ne_50m_glaciated_areas`\n- `ne_50m_lakes`\n- `ne_50m_lakes_historic`\n- `ne_50m_land`\n- `ne_50m_ocean`\n- `ne_50m_playas`\n- `ne_50m_populated_places`\n- `ne_50m_populated_places_simple`\n- `ne_50m_ports`\n- `ne_50m_rivers_lake_centerlines`\n- `ne_50m_rivers_lake_centerlines_scale_rank`\n- `ne_50m_urban_areas`", "html": "<p>Natural Earth (<a href=\"https://www.naturalearthdata.com/\" rel=\"nofollow\">website</a>, <a href=\"https://en.wikipedia.org/wiki/Natural_Earth\" rel=\"nofollow\">Wikipedia</a>) is a a public domain map dataset.</p>\n<p>It's distributed in a bunch of different formats - one of them is a SQLite database file.</p>\n<p><a href=\"http://naciscdn.org/naturalearth/packages/natural_earth_vector.sqlite.zip\" rel=\"nofollow\">http://naciscdn.org/naturalearth/packages/natural_earth_vector.sqlite.zip</a> - this is a 423MB file which decompresses to provide a 791MB <code>packages/natural_earth_vector.sqlite</code> file.</p>\n<p>I opened it in Datasette like this:</p>\n<pre><code>datasette --load-extension spatialite \\\n  ~/Downloads/natural_earth_vector.sqlite/packages/natural_earth_vector.sqlite\n</code></pre>\n<p>I had previously installed Datasette and SpatiaLite using Homebrew:</p>\n<pre><code>brew install datasette spatialite-tools\n</code></pre>\n<h2>\n<a id=\"user-content-database-format\" class=\"anchor\" href=\"#database-format\" aria-hidden=\"true\"><span aria-hidden=\"true\" class=\"octicon octicon-link\"></span></a>Database format</h2>\n<p>The database contains 181 tables, for different layers at different scales. Those tables are listed below.</p>\n<p>Each table has a bunch of columns and a <code>GEOMETRY</code> column. That geometry column contains data stored in WKB - Well-Known Binary format.</p>\n<p>If you have SpatiaLite you can convert that column to GeoJSON like so:</p>\n<pre><code>AsGeoJSON(GeomFromWKB(GEOMETRY))\n</code></pre>\n<p>For example, here are the largest \"urban areas\" at 50m scale:</p>\n<div class=\"highlight highlight-source-sql\"><pre><span class=\"pl-k\">select</span>\n  AsGeoJSON(GeomFromWKB(GEOMETRY))\n<span class=\"pl-k\">from</span>\n  ne_50m_urban_areas\n<span class=\"pl-k\">order by</span> area_sqkm <span class=\"pl-k\">desc</span></pre></div>\n<p>Every country at 50m scale (a good balance between detail and overall size):</p>\n<div class=\"highlight highlight-source-sql\"><pre><span class=\"pl-k\">select</span>\n  AsGeoJSON(GeomFromWKB(GEOMETRY)), <span class=\"pl-k\">*</span>\n<span class=\"pl-k\">from</span>\n  ne_50m_admin_0_countries</pre></div>\n<p>This query draws a coloured map of countries using the <code>datasette-geojson-map</code> and <code>sqlite-colorbrewer</code> plugins:</p>\n<div class=\"highlight highlight-source-sql\"><pre><span class=\"pl-k\">select</span>\n  ogc_fid,\n  GeomFromWKB(GEOMETRY) <span class=\"pl-k\">as</span> geometry,\n  colorbrewer(<span class=\"pl-s\"><span class=\"pl-pds\">'</span>Paired<span class=\"pl-pds\">'</span></span>, <span class=\"pl-c1\">9</span>, MAPCOLOR9 <span class=\"pl-k\">-</span> <span class=\"pl-c1\">1</span>) <span class=\"pl-k\">as</span> fill\n<span class=\"pl-k\">from</span>\n  ne_10m_admin_0_countries</pre></div>\n<p><a href=\"https://user-images.githubusercontent.com/9599/156858327-08f99300-29fd-4ca8-a268-f8c2ec659349.png\" target=\"_blank\" rel=\"nofollow\"><img width=\"1098\" alt=\"Screenshot of a map showing different countries in random colours\" src=\"https://user-images.githubusercontent.com/9599/156858327-08f99300-29fd-4ca8-a268-f8c2ec659349.png\" style=\"max-width:100%;\"></a></p>\n<p>The <code>ne_10m_admin_1_states_provinces</code> table is useful: it has subdivisions for a bunch of different countries. Here's the UK divided into counties:</p>\n<div class=\"highlight highlight-source-sql\"><pre><span class=\"pl-k\">select</span>\n  ogc_fid,\n  GeomFromWKB(GEOMETRY) <span class=\"pl-k\">as</span> geometry,\n  featurecla,\n  scalerank,\n  adm1_code,\n  diss_me,\n  iso_3166_2,\n  wikipedia,\n  iso_a2,\n  adm0_sr,\n  name,\n  name_alt,\n  type,\n  type_en,\n  area_sqkm,\n  latitude,\n  longitude,\n  admin\n<span class=\"pl-k\">from</span>\n  ne_10m_admin_1_states_provinces\n<span class=\"pl-k\">where</span>\n  admin <span class=\"pl-k\">=</span> <span class=\"pl-s\"><span class=\"pl-pds\">'</span>United Kingdom<span class=\"pl-pds\">'</span></span></pre></div>\n<p>I tried this with <code>select *, GeomFromWKB(GEOMETRY) as geometry</code> first but it didn't work with <code>datasette-geojson-map</code> because the <code>*</code> picked up the original <code>GEOMETRY</code> column in the wrong format.</p>\n<p>The scales are:</p>\n<ul>\n<li>Large scale data, 1:10m - most detailed</li>\n<li>Medium scale data, 1:50m</li>\n<li>Small scale data, 1:110m - least detailed</li>\n</ul>\n<h2>\n<a id=\"user-content-exploring-with-datasette-plugins\" class=\"anchor\" href=\"#exploring-with-datasette-plugins\" aria-hidden=\"true\"><span aria-hidden=\"true\" class=\"octicon octicon-link\"></span></a>Exploring with Datasette plugins</h2>\n<p>With the <code>datasette-leaflet-geojson</code> plugin installed, any column that returns GeoJSON (from <code>AsGeoJSON(GeomFromWKB(GEOMETRY))</code>) will render as a little map, no matter what the column name.</p>\n<p>If you install <code>datasette-geojson-map</code> you can seee a single map with all of the shapes on - you need to create a <code>geometry</code> column containing a SpatiaLite geometry, which you can do like this:</p>\n<div class=\"highlight highlight-source-sql\"><pre><span class=\"pl-k\">select</span>\n  ogc_fid, GeomFromWKB(GEOMETRY) <span class=\"pl-k\">as</span> geometry, <span class=\"pl-k\">*</span>\n<span class=\"pl-k\">from</span>\n  ne_50m_coastline</pre></div>\n<h2>\n<a id=\"user-content-full-list-of-tables\" class=\"anchor\" href=\"#full-list-of-tables\" aria-hidden=\"true\"><span aria-hidden=\"true\" class=\"octicon octicon-link\"></span></a>Full list of tables</h2>\n<ul>\n<li><code>ne_10m_admin_0_antarctic_claim_limit_lines</code></li>\n<li><code>ne_10m_admin_0_antarctic_claims</code></li>\n<li><code>ne_10m_admin_0_boundary_lines_disputed_areas</code></li>\n<li><code>ne_10m_admin_0_boundary_lines_land</code></li>\n<li><code>ne_10m_admin_0_boundary_lines_map_units</code></li>\n<li><code>ne_10m_admin_0_boundary_lines_maritime_indicator</code></li>\n<li><code>ne_10m_admin_0_boundary_lines_maritime_indicator_chn</code></li>\n<li><code>ne_10m_admin_0_countries</code></li>\n<li><code>ne_10m_admin_0_countries_arg</code></li>\n<li><code>ne_10m_admin_0_countries_bdg</code></li>\n<li><code>ne_10m_admin_0_countries_bra</code></li>\n<li><code>ne_10m_admin_0_countries_chn</code></li>\n<li><code>ne_10m_admin_0_countries_deu</code></li>\n<li><code>ne_10m_admin_0_countries_egy</code></li>\n<li><code>ne_10m_admin_0_countries_esp</code></li>\n<li><code>ne_10m_admin_0_countries_fra</code></li>\n<li><code>ne_10m_admin_0_countries_gbr</code></li>\n<li><code>ne_10m_admin_0_countries_grc</code></li>\n<li><code>ne_10m_admin_0_countries_idn</code></li>\n<li><code>ne_10m_admin_0_countries_ind</code></li>\n<li><code>ne_10m_admin_0_countries_isr</code></li>\n<li><code>ne_10m_admin_0_countries_ita</code></li>\n<li><code>ne_10m_admin_0_countries_jpn</code></li>\n<li><code>ne_10m_admin_0_countries_kor</code></li>\n<li><code>ne_10m_admin_0_countries_lakes</code></li>\n<li><code>ne_10m_admin_0_countries_mar</code></li>\n<li><code>ne_10m_admin_0_countries_nep</code></li>\n<li><code>ne_10m_admin_0_countries_nld</code></li>\n<li><code>ne_10m_admin_0_countries_pak</code></li>\n<li><code>ne_10m_admin_0_countries_pol</code></li>\n<li><code>ne_10m_admin_0_countries_prt</code></li>\n<li><code>ne_10m_admin_0_countries_pse</code></li>\n<li><code>ne_10m_admin_0_countries_rus</code></li>\n<li><code>ne_10m_admin_0_countries_sau</code></li>\n<li><code>ne_10m_admin_0_countries_swe</code></li>\n<li><code>ne_10m_admin_0_countries_tur</code></li>\n<li><code>ne_10m_admin_0_countries_twn</code></li>\n<li><code>ne_10m_admin_0_countries_ukr</code></li>\n<li><code>ne_10m_admin_0_countries_usa</code></li>\n<li><code>ne_10m_admin_0_countries_vnm</code></li>\n<li><code>ne_10m_admin_0_disputed_areas</code></li>\n<li><code>ne_10m_admin_0_disputed_areas_scale_rank_minor_islands</code></li>\n<li><code>ne_10m_admin_0_label_points</code></li>\n<li><code>ne_10m_admin_0_map_subunits</code></li>\n<li><code>ne_10m_admin_0_map_units</code></li>\n<li><code>ne_10m_admin_0_names</code></li>\n<li><code>ne_10m_admin_0_pacific_groupings</code></li>\n<li><code>ne_10m_admin_0_scale_rank</code></li>\n<li><code>ne_10m_admin_0_scale_rank_minor_islands</code></li>\n<li><code>ne_10m_admin_0_seams</code></li>\n<li><code>ne_10m_admin_0_sovereignty</code></li>\n<li><code>ne_10m_admin_1_label_points</code></li>\n<li><code>ne_10m_admin_1_label_points_details</code></li>\n<li><code>ne_10m_admin_1_seams</code></li>\n<li><code>ne_10m_admin_1_sel</code></li>\n<li><code>ne_10m_admin_1_states_provinces</code></li>\n<li><code>ne_10m_admin_1_states_provinces_lakes</code></li>\n<li><code>ne_10m_admin_1_states_provinces_lines</code></li>\n<li><code>ne_10m_admin_1_states_provinces_scale_rank</code></li>\n<li><code>ne_10m_admin_1_states_provinces_scale_rank_minor_islands</code></li>\n<li><code>ne_10m_admin_2_counties</code></li>\n<li><code>ne_10m_admin_2_counties_lakes</code></li>\n<li><code>ne_10m_admin_2_counties_lines</code></li>\n<li><code>ne_10m_admin_2_counties_scale_rank</code></li>\n<li><code>ne_10m_admin_2_counties_scale_rank_minor_islands</code></li>\n<li><code>ne_10m_admin_2_counties_to_match</code></li>\n<li><code>ne_10m_admin_2_label_points</code></li>\n<li><code>ne_10m_admin_2_label_points_details</code></li>\n<li><code>ne_10m_airports</code></li>\n<li><code>ne_10m_antarctic_ice_shelves_lines</code></li>\n<li><code>ne_10m_antarctic_ice_shelves_polys</code></li>\n<li><code>ne_10m_coastline</code></li>\n<li><code>ne_10m_geographic_lines</code></li>\n<li><code>ne_10m_geography_marine_polys</code></li>\n<li><code>ne_10m_geography_regions_elevation_points</code></li>\n<li><code>ne_10m_geography_regions_points</code></li>\n<li><code>ne_10m_geography_regions_polys</code></li>\n<li><code>ne_10m_glaciated_areas</code></li>\n<li><code>ne_10m_lakes</code></li>\n<li><code>ne_10m_lakes_australia</code></li>\n<li><code>ne_10m_lakes_europe</code></li>\n<li><code>ne_10m_lakes_historic</code></li>\n<li><code>ne_10m_lakes_north_america</code></li>\n<li><code>ne_10m_lakes_pluvial</code></li>\n<li><code>ne_10m_land</code></li>\n<li><code>ne_10m_land_ocean_label_points</code></li>\n<li><code>ne_10m_land_ocean_seams</code></li>\n<li><code>ne_10m_land_scale_rank</code></li>\n<li><code>ne_10m_minor_islands</code></li>\n<li><code>ne_10m_minor_islands_coastline</code></li>\n<li><code>ne_10m_minor_islands_label_points</code></li>\n<li><code>ne_10m_ocean</code></li>\n<li><code>ne_10m_ocean_scale_rank</code></li>\n<li><code>ne_10m_parks_and_protected_lands_area</code></li>\n<li><code>ne_10m_parks_and_protected_lands_line</code></li>\n<li><code>ne_10m_parks_and_protected_lands_point</code></li>\n<li><code>ne_10m_parks_and_protected_lands_scale_rank</code></li>\n<li><code>ne_10m_playas</code></li>\n<li><code>ne_10m_populated_places</code></li>\n<li><code>ne_10m_populated_places_simple</code></li>\n<li><code>ne_10m_ports</code></li>\n<li><code>ne_10m_railroads</code></li>\n<li><code>ne_10m_railroads_north_america</code></li>\n<li><code>ne_10m_reefs</code></li>\n<li><code>ne_10m_rivers_australia</code></li>\n<li><code>ne_10m_rivers_europe</code></li>\n<li><code>ne_10m_rivers_lake_centerlines</code></li>\n<li><code>ne_10m_rivers_lake_centerlines_scale_rank</code></li>\n<li><code>ne_10m_rivers_north_america</code></li>\n<li><code>ne_10m_roads</code></li>\n<li><code>ne_10m_roads_north_america</code></li>\n<li><code>ne_10m_time_zones</code></li>\n<li><code>ne_10m_urban_areas</code></li>\n<li><code>ne_10m_urban_areas_landscan</code></li>\n<li><code>ne_110m_admin_0_boundary_lines_land</code></li>\n<li><code>ne_110m_admin_0_countries</code></li>\n<li><code>ne_110m_admin_0_countries_lakes</code></li>\n<li><code>ne_110m_admin_0_map_units</code></li>\n<li><code>ne_110m_admin_0_pacific_groupings</code></li>\n<li><code>ne_110m_admin_0_scale_rank</code></li>\n<li><code>ne_110m_admin_0_sovereignty</code></li>\n<li><code>ne_110m_admin_0_tiny_countries</code></li>\n<li><code>ne_110m_admin_1_states_provinces</code></li>\n<li><code>ne_110m_admin_1_states_provinces_lakes</code></li>\n<li><code>ne_110m_admin_1_states_provinces_lines</code></li>\n<li><code>ne_110m_admin_1_states_provinces_scale_rank</code></li>\n<li><code>ne_110m_coastline</code></li>\n<li><code>ne_110m_geographic_lines</code></li>\n<li><code>ne_110m_geography_marine_polys</code></li>\n<li><code>ne_110m_geography_regions_elevation_points</code></li>\n<li><code>ne_110m_geography_regions_points</code></li>\n<li><code>ne_110m_geography_regions_polys</code></li>\n<li><code>ne_110m_glaciated_areas</code></li>\n<li><code>ne_110m_lakes</code></li>\n<li><code>ne_110m_land</code></li>\n<li><code>ne_110m_ocean</code></li>\n<li><code>ne_110m_populated_places</code></li>\n<li><code>ne_110m_populated_places_simple</code></li>\n<li><code>ne_110m_rivers_lake_centerlines</code></li>\n<li><code>ne_50m_admin_0_boundary_lines_disputed_areas</code></li>\n<li><code>ne_50m_admin_0_boundary_lines_land</code></li>\n<li><code>ne_50m_admin_0_boundary_lines_maritime_indicator</code></li>\n<li><code>ne_50m_admin_0_boundary_lines_maritime_indicator_chn</code></li>\n<li><code>ne_50m_admin_0_boundary_map_units</code></li>\n<li><code>ne_50m_admin_0_breakaway_disputed_areas</code></li>\n<li><code>ne_50m_admin_0_breakaway_disputed_areas_scale_rank</code></li>\n<li><code>ne_50m_admin_0_countries</code></li>\n<li><code>ne_50m_admin_0_countries_lakes</code></li>\n<li><code>ne_50m_admin_0_map_subunits</code></li>\n<li><code>ne_50m_admin_0_map_units</code></li>\n<li><code>ne_50m_admin_0_pacific_groupings</code></li>\n<li><code>ne_50m_admin_0_scale_rank</code></li>\n<li><code>ne_50m_admin_0_sovereignty</code></li>\n<li><code>ne_50m_admin_0_tiny_countries</code></li>\n<li><code>ne_50m_admin_0_tiny_countries_scale_rank</code></li>\n<li><code>ne_50m_admin_1_seams</code></li>\n<li><code>ne_50m_admin_1_states_provinces</code></li>\n<li><code>ne_50m_admin_1_states_provinces_lakes</code></li>\n<li><code>ne_50m_admin_1_states_provinces_lines</code></li>\n<li><code>ne_50m_admin_1_states_provinces_scale_rank</code></li>\n<li><code>ne_50m_airports</code></li>\n<li><code>ne_50m_antarctic_ice_shelves_lines</code></li>\n<li><code>ne_50m_antarctic_ice_shelves_polys</code></li>\n<li><code>ne_50m_coastline</code></li>\n<li><code>ne_50m_geographic_lines</code></li>\n<li><code>ne_50m_geography_marine_polys</code></li>\n<li><code>ne_50m_geography_regions_elevation_points</code></li>\n<li><code>ne_50m_geography_regions_points</code></li>\n<li><code>ne_50m_geography_regions_polys</code></li>\n<li><code>ne_50m_glaciated_areas</code></li>\n<li><code>ne_50m_lakes</code></li>\n<li><code>ne_50m_lakes_historic</code></li>\n<li><code>ne_50m_land</code></li>\n<li><code>ne_50m_ocean</code></li>\n<li><code>ne_50m_playas</code></li>\n<li><code>ne_50m_populated_places</code></li>\n<li><code>ne_50m_populated_places_simple</code></li>\n<li><code>ne_50m_ports</code></li>\n<li><code>ne_50m_rivers_lake_centerlines</code></li>\n<li><code>ne_50m_rivers_lake_centerlines_scale_rank</code></li>\n<li><code>ne_50m_urban_areas</code></li>\n</ul>\n", 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"}, 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