Evaluation of the performance of snow and water spectral indices for the separation of water and snow/ice cover (SCG) features

Due to climate change and reduction of precipitation as one of its main components, especially in the mountainous areas of the northwest of Iran, it is important to study the important phenomenon of water and snow due to the importance of snow reservoirs in feeding water reserves. Due to the importance of spectral indices in measuring distance and spectral similarity of snow and water phenomena, in the present study, normalized indices of normalized water and snow, as well as normalized indices without snow/ice and water background and Otsu threshold method on the image Landsat 8, has been used as a study area by selecting a part of Sabalan Mountain and the Caspian Sea. The results of the present study showed that, according to the histogram and variance of the bands, the normalized differential indices of water without snow and snow without water, with 100% accuracy and 97% accuracy, respectively, showed high accuracy in extracting and separating water and snow cover phenomena. The results of the implementation of the Otsu binary algorithm also confirmed this and showed the high ability of the desired indicators to extract snow and water phenomena.