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

نوع مقاله : مقاله پژوهشی

نویسندگان

Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran

چکیده

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-2 and Landsat satellite imagery from snow cover seasons between 2021 to 2024, alongside several snow indices (NDSI, NDSII, NDSInw, S3, 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 S3 and SWI indices provided the highest accuracy in snow detection, with Sentinel-2 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.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

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

نویسندگان [English]

  • Batool Zeinali
  • Sina Khonkham
  • Sayyad Asghari Saraskanroud
Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran
چکیده [English]

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-2 and Landsat satellite imagery from snow cover seasons between 2021 to 2024, alongside several snow indices (NDSI, NDSII, NDSInw, S3, 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 S3 and SWI indices provided the highest accuracy in snow detection, with Sentinel-2 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.

کلیدواژه‌ها [English]

  • Snow Mapping
  • Topographic variables
  • Sentinel-2
  • Landsat
  • Spectral Indices

مراجع

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پژوهشهای دانش زمین
دوره 16، Special Issue - شماره پیاپی 64
Special Issue
آذر 1404
صفحه 182-192

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