Climatology
Narges Samadi; Ali akbar Rasouli pirouzian; Davood Mokhtari; Khalil Valizadeh Kamran
Abstract
The main aim of the current study was to detect changes in snow cover within the Western watersheds of Lake Urmia, situated in the Silvaneh mountain range, using the processing of multi-sensor and multi-spectral satellite images for high-precision identification of snow-covered areas. Sentinel-2 and ...
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The main aim of the current study was to detect changes in snow cover within the Western watersheds of Lake Urmia, situated in the Silvaneh mountain range, using the processing of multi-sensor and multi-spectral satellite images for high-precision identification of snow-covered areas. Sentinel-2 and Landsat (8 and 9) satellite images were acquired and underwent preprocessing operations, such as atmospheric and radiometric corrections, using ENVI software version 1/10. Projects for the May months of the years 2016 to 2023 were then established. Initially, normalized difference snow indices were employed to independently generate snow cover maps for Landsat and Sentinel images for the entire watersheds of Nazluchay, Ruzechay, Shahrchay, and Barandozchay. In the next stage, an optimized color-sensitive object-based approach, based on object-oriented functions, was applied to the main bands of the Sentinel-2 sensor. To enhance the accuracy of the final results, Landsat images were fused with Sentinel images through a coordinated fusion method, producing various products, especially high-resolution optimized color images and classified scene maps. Ultimately, high-precision snow cover maps for temporal series were extracted for each of the mentioned watersheds through processing the fused images. Examination of the snow cover maps revealed that despite its smaller area compared to the Nazluchay and Barandozchay watersheds, the Shahrchay watershed has a higher snow accumulation coefficient, allowing for greater snow cover storage. Additionally, the comparison of the snow cover density map (years 2016 to 2023) with the elevation model of Alouspalsar at a resolution of 5/12 meters indicates a significant distribution of snow cover in higher elevations above 2300 meters in the study area. Therefore, accurate identification of snow cover, even on a daily and weekly scale, can provide essential and precise information for proactive water resource management, resulting from snowmelt, with multiple objectives in the watersheds surrounding Lake Urmia.
