GIS & Remote Sensing

Remote sensing is only useful if the signal survives contact with the real ground.

I build spatial analysis and remote-sensing workflows that span turbidity mapping, satellite imagery QC, oceanographic feature detection, and land-suitability analysis — always validated against what's actually observable on the ground, not just what the raster says.

• Mapped monthly turbidity patterns in Google Earth Engine to identify potential siltation zones.
• Processed multi-year NetCDF datasets in Python to detect mesoscale ocean eddies and track their lifecycle.
• Conducted QC and validation of satellite imagery datasets used for AI model training and evaluation.
• Performed suitability mapping integrating land use, terrain, and environmental constraints for nature-based solutions siting.