This evaluation identifies water extraction indices like NDWI and WRI in Ethiopia, suggesting their utility in precise GIS applications.
This study evaluates various water extraction indices to identify surface features using Sentinel-2 satellite images. Eight study sites were selected with three indices employed in this study, such as the water ratio index (WRI), the modified normalized difference water index (MNDWI), and the normalized difference water index (NDWI). The results of the accuracy assessment revealed that the producer accuracy (PA) for the NDWI ranged from 81.11 to 94.56%, that for the MNDWI ranged from 85.3 to 96.7%, and that for the WRI ranged from 96.98 to 97.98%. The user accuracies for the NDWI, MNDWI, and WRI results are 68.1–81.6%, 74.81–86.14%, and 80.33–88.78%, respectively. This study reveals that the WRI has greater PA (97.98%), user accuracy (88.78%), and kappa statistic (0.88) than the MNDWI and NDWI. The WRI is particularly suitable for extracting surface bodies surrounded by bare lands with minimal vegetation cover. Conversely, the NDWI is more applicable in areas with moderate vegetation and shadows, such as agricultural regions or wetlands. The MNDWI is suitable to avoid confusion water bodies with built-up areas and used to extract water bodies with various land cover. Therefore, establishing optimal thresholds is essential for policymakers and planners to effectively monitor water surface features and changes in water sources.
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Girma et al. (2025) studied this question.
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