Augmented Normalized Difference Water Index for improved surface water monitoring

We present a comprehensive critical review of well-established satellite remote sensing water indices and offer novel, robust Augmented Normalized Difference Water Index (ANDWI). ANDWI employs an expanded set spectral bands, RGB, NIR, SWIR1-2, to maximize the contrast between non-water pixels. Further, we implement dynamic thresholding method, Otsu algorithm, enhance ANDWI's performance. Applied variety environmental conditions, with Otsu-thresholding offered highest overall accuracy (accuracy = 0.98, F1 Kappa 0.96) compared other (NDWI, MNDWI, AWEI, WI). also propose novel cloud filtering algorithm that substantially increases number useable images conventional cloud-free composites (124% increased observations in studied area) resolves inappropriate masking bodies hot sands as clouds by methods. Finally, develop Google Earth Engine App readily delineate 16-day surface across globe.