GeoJSON

GeoJSON
Name	GeoJSON
Type	File format
Owner	Internet Engineering Task Force
Released	2008
Extension	.json
Mime	application/geo+json
Website	IETF

GeoJSON is an open format for encoding geographic data structures using a subset of JavaScript Object Notation designed for interoperability among mapping systems, web services, and spatial databases. It enables representation of points, lines, polygons, and collections in a human-readable text form suitable for APIs, web mapping, and data interchange across platforms like OpenStreetMap, Google Maps, Mapbox, and Esri. The format's simplicity and compatibility with Mozilla Firefox, Google Chrome, and server frameworks such as Node.js and Django have driven broad adoption across industry, academia, and government agencies including USGS, NOAA, and the European Space Agency.

Overview

GeoJSON derives structure from JavaScript and RFC 4627 JSON conventions and was standardized by the Internet Engineering Task Force through an RFC 7946 process involving contributors from organizations such as Mapbox, Esri, and OpenLayers. It is used with web protocols implemented in Apache HTTP Server, nginx, and Amazon Web Services APIs to transfer geospatial features between clients like QGIS, ArcGIS, and browsers running Leaflet. GeoJSON's text-based nature allows integration with Git, GitHub, and continuous integration pipelines used by projects like Natural Earth and Humanitarian OpenStreetMap Team.

Specification

The specification defines JSON objects for spatial types and associated properties, aligning with requirements from IETF working groups and influenced by earlier standards such as OGC formats and KML from Google Earth. It prescribes required keys and value types so implementations in PostGIS, SpatiaLite, and MongoDB maintain consistency. RFC-driven decisions affected interactions with WGS 84 and conventions used by agencies like NOAA and National Geospatial-Intelligence Agency.

Geometry Types

GeoJSON supports a finite set of geometry JSON objects used in GIS workflows common to USGS datasets and projects like OpenStreetMap. Geometries include: - Point — used for entities like records from Global Positioning System surveys, placemarks in Google Earth, and sensor locations for Copernicus Programme. - MultiPoint — suitable for collections such as UN-managed refugee camp markers or sampling stations from World Health Organization studies. - LineString — models routes like Pan-American Highway segments, Trans-Siberian Railway tracks, and river courses managed by UNESCO. - MultiLineString — represents route networks for agencies like Federal Aviation Administration and International Maritime Organization. - Polygon — encodes boundaries for areas such as Yellowstone National Park, CERN facilities, and administrative units used by United Nations databases. - MultiPolygon — captures complex territories like archipelagos referenced by European Union statistics and maritime zones under United Nations Convention on the Law of the Sea. - GeometryCollection — aggregates heterogeneous geometries for composite datasets used in projects led by National Aeronautics and Space Administration and European Space Agency.

Features and FeatureCollections

GeoJSON introduces Feature objects pairing a geometry with a properties object to represent real-world entities analogous to records in OpenStreetMap and layers in ArcGIS Online. FeatureCollections aggregate multiple Features for transport in APIs such as CartoDB services, bulk exports from QGIS, and tiling pipelines employed by Mapbox and Google Cloud Platform. These constructs facilitate interoperability with standards like ISO 19115 metadata and workflows in GDAL/OGR utilities.

Coordinate Reference System and Precision

The specification mandates use of World Geodetic System 1984 coordinates for long-term consistency, reflecting practice in NOAA and USGS datasets. Coordinates are ordered as longitude, latitude, with an optional altitude value compatible with EPSG:4326 conventions used by many national mapping agencies. Precision considerations affect storage and rendering in systems such as PostGIS and Cesium (software), and influence quantization and simplification algorithms employed in Douglas–Peucker algorithm implementations used by mapping libraries.

Implementations and Libraries

GeoJSON is implemented across a wide ecosystem: server-side stacks like Node.js with modules in npm, Python libraries such as GeoPandas and Shapely, Java tools including GeoTools, C++ components in GDAL/OGR, and client frameworks like OpenLayers and Leaflet (software). Databases with native GeoJSON support include MongoDB, PostgreSQL with PostGIS, and cloud platforms like Amazon Aurora and Google BigQuery. Visualization and tiling systems from Mapbox, Esri, and Mapnik consume GeoJSON for vector tiles and styling.

Use Cases and Applications

GeoJSON is widely used for web mapping in projects like OpenStreetMap, disaster response by Red Cross, environmental monitoring by United Nations Environment Programme, urban planning in municipal systems of cities such as New York City and London, and mobile location services from companies like Uber (company) and Airbnb. Scientific workflows in National Oceanic and Atmospheric Administration research, biodiversity portals like Global Biodiversity Information Facility, and heritage inventories managed by UNESCO also employ GeoJSON for data exchange, visualization, and integration with machine learning pipelines in platforms such as TensorFlow.

Category:Geographic data formats