Integrated remote sensing analysis of snow cover and topographic influences in mountainous regions (Case study: Marivan County, Iran)

Snow plays a vital role in the hydrological cycle, especially in mountainous regions, significantly affecting water resources, agriculture, and natural hazard mitigation. This study employs remote sensing data to analyze the spatiotemporal distribution of snow cover and its relationship with precipitation and topographic variables, including slope, aspect, and elevation in Marivan County, western Iran. Sentinel-۲ and Landsat satellite imagery from snow cover seasons between ۲۰۲۱ to ۲۰۲۴, alongside several snow indices (NDSI, NDSII, NDSInw, S۳, SWI and NBSI-MS), were used to generate snow cover maps. Satellite-based precipitation datasets (CHIRPS and PERSIANN) were utilized to explore correlation between snow cover and precipitation patterns. Results indicated that the S۳ and SWI indices provided the highest accuracy in snow detection, with Sentinel-۲ imagery outperforming Landsat due to its finer spatial resolution. Topographic analysis revealed that regions with higher elevation, northern aspect and gentle slopes had the densest snow cover. Overall, this study highlights that effectiveness of intergrating optical remote sensing, precipitation data, and topographic information for accurate monitoring of snow cover in mountainous areas.

کلیدواژه ها:

Snow Mapping ، Topographic variables ، Sentinel-۲ ، Landsat ، Spectral Indices