Apply high-resolution PlanetScope data to generate near-real-time environmental monitoring insights.

Developing and validating machine-learning models for crop-residue burning detection using high-temporal multispectral satellite data (Sentinel-2, PlanetScope, VIIRS). Applying remote sensing analytics, spectral index design, and Google Earth Engine with cloud computing and HPC-enabled batch processing.

Modelled and visualised fire dispersion paths using the HYSPLIT atmospheric transport model in Python and R on high-performance computing infrastructure. Structured spatial data into standardised, research-ready formats.