{"id": "spatialite:importing-shapefiles-into-spatialite", "page": "spatialite", "ref": "importing-shapefiles-into-spatialite", "title": "Importing shapefiles into SpatiaLite", "content": "The  shapefile format  is a common format for distributing geospatial data. You can use the  spatialite  command-line tool to create a new database table from a shapefile. \n             Try it now with the North America shapefile available from the University of North Carolina  Global River Database  project. Download the file and unzip it (this will create files called  narivs.dbf ,  narivs.prj ,  narivs.shp  and  narivs.shx  in the current directory), then run the following: \n             spatialite rivers-database.db \n             SpatiaLite version ..: 4.3.0a       Supported Extensions:\n...\nspatialite> .loadshp narivs rivers CP1252 23032\n========\nLoading shapefile at 'narivs' into SQLite table 'rivers'\n...\nInserted 467973 rows into 'rivers' from SHAPEFILE \n             This will load the data from the  narivs  shapefile into a new database table called  rivers . \n             Exit out of  spatialite  (using  Ctrl+D ) and run Datasette against your new database like this: \n             datasette rivers-database.db \\\n    --load-extension=/usr/local/lib/mod_spatialite.dylib \n             If you browse to  http://localhost:8001/rivers-database/rivers  you will see the new table... but the  Geometry  column will contain unreadable binary data (SpatiaLite uses  a custom format based on WKB ). \n             The easiest way to turn this into semi-readable data is to use the SpatiaLite  AsGeoJSON  function. Try the following using the SQL query interface at  http://localhost:8001/rivers-database : \n             select *, AsGeoJSON(Geometry) from rivers limit 10; \n             This will give you back an additional column of GeoJSON. You can copy and paste GeoJSON from this column into the debugging tool at  geojson.io  to visualize it on a map. \n             To see a more interesting example, try ordering the records with the longest geometry first. Since there are 467,000 rows in the table you will first need to increase the SQL time limit imposed by Datasette: \n             datasette rivers-database.db \\\n    --load-extension=/usr/local/lib/mod_spatialite.dylib \\\n    --setting sql_time_limit_ms 10000 \n             Now try the following query: \n             select *, AsGeoJSON(Geometry) from rivers\norder by length(Geometry) desc limit 10;", "breadcrumbs": "[\"SpatiaLite\"]", "references": "[{\"href\": \"https://en.wikipedia.org/wiki/Shapefile\", \"label\": \"shapefile format\"}, {\"href\": \"http://gaia.geosci.unc.edu/rivers/\", \"label\": \"Global River Database\"}, {\"href\": \"https://www.gaia-gis.it/gaia-sins/BLOB-Geometry.html\", \"label\": \"a custom format based on WKB\"}, {\"href\": \"https://geojson.io/\", \"label\": \"geojson.io\"}]"}