Prompt
geospatial data API
Latest observation
A geospatial data API is an API that lets you store, query, analyze, and visualize location-based data like points, lines, polygons, tiles, and GPS traces.
Common capabilities
- Geocoding / reverse geocoding: address ↔ coordinates
- Spatial queries: “find all points within 5 km”
- Map rendering: vector/raster tiles
- Routing / directions: shortest path, ETA
- Spatial analysis: distance, containment, intersection, clustering
- Feature storage: GeoJSON, PostGIS, shapefiles, etc.
Typical data formats
- GeoJSON
- KML
- WKT / WKB
- MBTiles
- GeoParquet
- PostGIS geometries
Example use cases
- Delivery tracking
- Store locator search
- Disaster response mapping
- Fleet routing
- Environmental monitoring
- Urban planning
Example API endpoints
GET /places?lat=40.7&lon=-74.0&radius=5000
POST /geocode
POST /route
GET /tiles/{z}/{x}/{y}
Popular geospatial APIs/tools
- Google Maps Platform
- Mapbox
- OpenStreetMap-based APIs
- ArcGIS API
- PostGIS for spatial databases
- GeoServer
- Overpass API (OpenStreetMap data)
If you want to build one
A common stack is:
- Database: PostgreSQL + PostGIS
- API layer: FastAPI / Flask / Node.js
- Map rendering: Mapbox GL / Leaflet / OpenLayers
- Data format: GeoJSON for responses
If you want, I can also help with:
- Designing a geospatial API
- Writing sample endpoints
- Choosing a geospatial database
- Building one in Python/Node.js
Observation history
How did Obsurfable measure this prompt?
Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.
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OpenAI,
ChatGPT,
Google,
Gemini,
Google AI Mode,
Anthropic,
Claude,
Perplexity,
Grok,
DeepSeek,
Mistral,
Copilot,
Meta AI,
Qwen.
How can brands improve their AEO?
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