Evaluating the Efficiency of Vegetation Indices (NDVI, SAVI, EVI, WDVI) in Monitoring Vegetation Cover in Arid and Semi-Arid Regions: A Case Study of the Wadi Mansour Basin
DOI:
https://doi.org/10.5281/zenodo.22738828Keywords:
Satellite Imagery, Wadi Mansour Basin, Vegetation Cover Remote SensingAbstract
This study aims to evaluate the efficiency of four spectral vegetation indices (NDVI, SAVI, EVI, and WDVI) in monitoring vegetation cover within the Wadi Mansour Basin, an arid basin located in northwestern Libya, specifically in the Bani Walid region.
The methodology relied on Landsat-8 satellite imagery acquired in March 2025. The study classified vegetation cover into three primary categories, assessing the accuracy of the results using 30 reference points collected via stratified random sampling.
The results demonstrated the superiority of the SAVI index as the most efficient tool for monitoring vegetation, achieving an Overall Accuracy of approximately 93.3% and a Kappa Coefficient of 0.85. This performance is attributed to its high capability in minimizing soil background interference. Conversely, error matrices revealed a tendency in the NDVI index to overestimate vegetation density. The EVI index showed conservative results in detecting sparse vegetation, while the WDVI index exhibited high sensitivity to the soil line, which affected its accuracy across certain categories.
The study concludes the significance of utilizing soil-adjusted vegetation indices when studying arid and semi-arid environments, given their role in enhancing the accuracy of spatial representation for vegetation and increasing the reliability of the findings.
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