Rohma Shakoor
Gis and Remote sensing analyst
Unpopular opinion: 90% of the complex Machine Learning models built for satellite remote sensing are completely unnecessary.
We see fancy Deep Learning architectures deployed just to map basic surface water, vegetation stress, or land cover—when a well-calibrated physical index...
Can satellite machine learning tell a felled forest from a harvested field? 🛰️
At 10 metres, the answer is: only if your feature stack and your validation are built for it.
Most land-cover maps break at exactly this problem — forest loss and agricultural cycles look similar in a...
Mapping Flood Vulnerability: Flood Risk Assessment of Sindh, Pakistan (2025).
My latest spatial analysis project focusing on inundation dynamics and surface water occurrence across the Sindh province!
Using Multi-Criteria Decision Analysis (MCDA), satellite remote sensing, and...
Supervised Land Use Land Cover (LULC) Classification of Chiniot (1990–2023)
50-Year Flood Inundation & Critical Asset Risk Engine for Pakistan
