Selected Projects

Geospatial datasets often contain geometry errors and coordinate reference inconsistencies that break analysis workflows.

Vector datasets (Shapefiles, GeoJSON, PostGIS layers).

Designed and developed a modular Python library to detect, validate, repair, and report geometry and CRS issues using automated checks and spatial validation routines.

Reduced manual preprocessing effort and improved reliability of spatial data pipelines.

Infrastructure planning requires spatial identification of high-risk landslide zones.

Terrain data (DEM), geological layers, land use, slope, environmental factors.

Built a spatial modelling workflow to generate susceptibility maps and deployed results through a WebGIS interface using GeoServer and web layers.

Delivered interactive spatial risk visualization for decision support.

Rapid urban expansion required structured spatial analysis of land-use change over time.

Multi-temporal satellite imagery, NDVI/NDWI indices, urban classification layers.

Designed an ML-based classification workflow to process satellite imagery and quantify urban expansion trends over two decades.

Generated spatial growth maps and quantified land-use transformation patterns.

Air quality data lacked structured visualization and accessible analytics for users.

Real-time environmental sensor data and statistical datasets.

Developed an interactive dashboard integrating spatial visualization, data filtering, and role-based access control.

Enabled structured environmental monitoring and decision support.