Land Parcel Details App: GIS Developer Needed need Mobile App Development

Contact person: Land Parcel Details App: GIS Developer Needed

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Location: Ahmedabad, India

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"Job Post: GIS Developer + Full-Stack Engineer for Land Records + Maps MVP (Ahmedabad District)

Project Overview

I am building a pilot application that allows users to stand on a piece of land in Ahmedabad District (Gujarat, India) and instantly view its land parcel details (survey number / 7/12 extract reference) on a map.

I already have village cadastral maps in PDF format. The goal is to convert these into map overlays, integrate them with Google Maps (or open-source alternatives like Mapbox/MapLibre), and build a simple app (mobile/web) that shows the land parcel when the user shares their GPS location.


Phase 1 (Pilot Scope – 5 Villages)

1. GIS Data Processing

Convert village cadastral maps (PDF) into usable geospatial format.

If raster → georeference with known landmarks (roads, rivers, boundaries).

Export as GeoJSON / Shapefile / PostGIS-compatible polygons.



2. Backend Development

Set up PostgreSQL + PostGIS database.

API endpoint: input GPS (lat/lon) → return parcel polygon + survey number.

Spatial queries: ST_Contains, ST_Distance for nearest parcel lookup.

Host via Node.js/Python backend (REST/GraphQL).



3. Frontend (Basic App / Demo)

Web or Mobile (React / React Native / Flutter).

Map integration (Google Maps SDK OR MapLibre/Mapbox).

Show GPS blue dot, highlight parcel boundary, display survey number.

Required Skills

Strong GIS experience: QGIS, GDAL/OGR, map georeferencing.

Knowledge of PostGIS and spatial queries.

Experience with GeoServer / TileServer GL / vector tiles.

Backend development: Node.js / Python (FastAPI / Express).

Frontend: React / React Native / Flutter with Google Maps / MapLibre integration.

Ability to integrate AI/ML features in later phases (e.g., AI-powered land parcel recognition, OCR on land records, predictive insights)." (client-provided description)


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