Remote Sensing-Based Assessment of Spatio-Temporal Changes in Vegetation, Soil-Surface Condition, and Reservoir Extent around the Bin El Ouidane Dam (Central High Atlas, Morocco)
DOI:
https://doi.org/10.55779/ng63722Keywords:
Bin El Ouidane, Brightness Index, Coloration Index, Landsat, NDVI, NDWI, remote sensing, soil-surface conditionAbstract
Mountain watersheds in the Mediterranean region are highly susceptible to land degradation because steep slopes, variable rainfall, erodible substrates, and human pressure interact to accelerate runoff and sediment production. This study used Geographic Information Systems (GIS) and multi-temporal Landsat imagery to assess changes in vegetation cover, soil-surface condition, and reservoir extent around the Bin El Ouidane Dam in the Central High Atlas, Morocco, between 1987 and 2015. Landsat TM and Landsat 8 OLI/TIRS images with a spatial resolution of 30 m were processed, and four spectral indices were derived: the Normalized Difference Vegetation Index (NDVI), Brightness Index (BI), Coloration Index (CI), and Normalized Difference Water Index (NDWI). The mapped classes indicate an increase in dense vegetation from approximately 5% to 12% and in sparse vegetation from 17% to 20%, accompanied by a decline in bare or poorly vegetated surfaces from 73% to 60%. The soil-surface indices likewise show a reduction in the most exposed classes, although moderately degraded sectors remain extensive. NDWI-based mapping indicates an approximately 5.9% increase in mapped reservoir surface area between the two acquisition dates. Because the analysis compares two satellite snapshots, the observed changes should be interpreted as spatial associations rather than direct evidence of specific climatic or management causes. Overall, the results demonstrate the value of consistent spectral-index mapping for screening environmental change and prioritizing field verification and soil-conservation measures in mountainous watersheds.
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