Vegetation cover change is a key indicator of ecosystem health, soil moisture availability, and land degradation at global, regional, and local levels. Assessment of these changes is crucial to ensuring the sustainability of terrestrial ecosystems such as the Nzeeu River Catchment. The study aimed to determine land use and land cover changes, as well as drivers, in the Nzeeu River catchment for the period 2000 - 2023. The study employed a remote sensing workflow to analyze vegetation dynamics using the complete Landsat archive (Landsat 5 - 9) and Sentinel imagery, processed in Google Earth Engine. Cloud-free monthly composites were generated using median reducers, while atmospheric and cloud masking were implemented using quality assessment bands and the CFMask algorithm. Vegetation changes were assessed through post-classification comparison of annual land-cover maps generated via supervised classification to quantify transitions between cover types, and through continuous NDVI time-series analysis. Classification accuracy was evaluated using error matrices to calculate overall accuracy, producer’s/user’s accuracies, and kappa statistics. Overall accuracy for the classifications ranged from 92.57% for the year 2000 to 92.8%, 94.4%, and 94.9% for the years 2010, 2020, and 2023, respectively. Higher values were reported for the Kappa coefficient corresponding to 0.825, 0.83, 0.866 in 2020, and 0.879 in the years 2000, 2010, 2020, and 2023, respectively. The results of the classification and analysis process established that forest cover reduced from 39.95% to 27.54%, agriculture increased from 27.40% to 32.44%, shrubs increased from 28.13% to 33.61%, bare ground increased from 3% to 4.44%, and urban land cover increased from 1% to 2%. The main drivers of land use and land cover changes identified were agricultural expansion, urbanization and demographic pressures, hydrological interventions, climate variability, and environmental drivers.
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