Map of Sofala Province in GeoJSON format
A map built from OpenStreetMap data, ready to download
Customize the map
Open this place's area in the constructor and adjust everything to your needs
Open in constructor →Map passport
What this map contains by default
This is how the map is built as-is — every setting can be changed in the constructor.
Sobre GeoJSON
Map of Sofala Province in GeoJSON — an export of real OpenStreetMap data for the selected area.
Open text-based geodata format built on JSON. Widely supported by web mapping libraries, human-readable and easy to process with scripts.
Which layers are in the file
This file for the selected area contains:
- Roads
- Buildings
- Water
- Greenery
- Points of interest
Coordinate systems
WGS 84 (EPSG:4326), selectable in the wizard
Compatibility
Units
Meters (projected in the chosen coordinate system)
| Categoria | GIS |
| Extensió del fitxer | .geojson |
| Nivell | Free |
What's in the GeoJSON map of Sofala Province
978,277 buildings (2,832 residential, 16 commercial, 274 industrial, 5 religious), 22,237.3 km of roads, 364 points of interest, 14 landmarks.
Mostly unclassified roads 15,512.1 km, residential streets 2,502.5 km, tertiary roads 2,238.1 km.
Key amenities: colleges — 6, schools — 30, hospitals — 6.
GeoJSON contains 978,277 buildings and 364 POIs with coordinates, names and attributes. Ready for Leaflet, Mapbox, D3.js.
Main streets: Rua Carlos Pereira, Rua Dom Jaime Pedro Gonçalves, Ava Kruss Gomes, Rua Carlos Pereira, Armando Tivane
Landmarks: Lion House, Parque Nacional da Gorongosa, Igreja Católica de Luwati, Igreja Católica de Ntopa, Igreja Católica de cachorro
How to use GeoJSON for Sofala Province
- Select the Sofala Province area on the map
- Export to GeoJSON
- Load into QGIS, Mapbox Studio, or kepler.gl
- Use for analysis, filtering, and visualization
Programs that open GeoJSON
FAQ: GeoJSON for Sofala Province
How to open GeoJSON?
GeoJSON opens in QGIS, geojson.io, Mapbox Studio, kepler.gl, or any text editor — it's just JSON.
Is GeoJSON suitable for large areas?
For large areas, GeoPackage or FlatGeobuf is better — they're more compact and load faster.
