Multi-Temporal Remote Sensing Change Detection Using Google Earth Engine and Random Forest Classifiers
Multi-Temporal Remote Sensing Change Detection Using Google Earth Engine and Random Forest Classifiers Monitoring landscape transformations over decadal timescales requires moving beyond simple spectral indices. Traditional bi-temporal approaches—such as manual image differencing or post-classification comparison using heuristic thresholds—frequently fall short when applied to complex, multi-year land-use and land-cover (LULC) change detection. Factors like inter-annual phenological … Read more