Afshin Sotoudehpour; Aghil Madadi; sayyad Asghari
Abstract
Remote sensing data has played an important role in natural resource management studies in recent years. These data, especially in water resources studies and researches, have many uses. Among water-related studies, the use of water indexes in recent years has been widely considered.These indexes have ...
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Remote sensing data has played an important role in natural resource management studies in recent years. These data, especially in water resources studies and researches, have many uses. Among water-related studies, the use of water indexes in recent years has been widely considered.These indexes have grown and developed with the advancement and production of satellite images And their precision increased dramatically.In this research, Landsat 8 and Sentinel A2 satellite images were used on coast of Bushehr on the Persian Gulf. 8 water index were selected and executed on images.In spite of the fact to exist two clases water and land unsupervised classification was applied to images and Finally, The overall accuracy and kappa coefficient values range from 77.0% to 99.6% and 0.55 to 0.99 respectively. For Landsat images, the Modified Normalized Difference Water Index (MNDWI) and the Normalized Difference pond index (NDPI) were the best indexes.Water Ratio Index (WRI) and Normalized Difference Turbidity index (NDTI) were recognized as the worst index.For Sentinel 2A images, the Modified Normalized Difference Water Index (MNDWI) and the Normalized Water Difference Index (NDWI), respectively, were the best.and the Automatic Water Extraction Index (AWEI_NSH) had the worst result.In general, the performance of the water indexes, the accuracy level of the sentinel2A images was significantly higher than the Landsat 8 images This factor can be due to the higher spatial resolution of Sentinel images.For both Landsat 8 and Sentinel A2 images the Modified Normalized Difference Water Index (MNDWI) has the best results.