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Information Journal Paper

Title

Analysis of the consequences of climate change on the characteristics of middle Zagros snow cover using remote sensing data

Pages

  22-43

Abstract

Climate Change is a significant environmental concern due to the sensitivity of glacier melting processes and snow density to climate variations. Currently, a range of satellite sensors, including AVHRR, MODIS, GEOS, and MERIS, are employed for snow monitoring and are extensively utilized to analyze fluctuations and changes in global Snow cover. The Modis Sensor is particularly favored for its extensive global spatial coverage, suitable spatial accuracy, and frequent temporal coverage across various scales. Consequently, this study utilizes snow products derived from the Modis Sensor. In this investigation, data on snow-related days from the statistical period of 1989 to 2018 were collected for three provinces: Kermanshah, Ilam, and Lorestan. This data was processed using MODIS Snow cover information pertinent to the Middle Zagros region, in conjunction with Remote Sensing techniques. The study provides a detailed examination of Snow cover changes within the specified area. The Normalized Difference Snow Index (NDSI) was employed to detect Snow cover within the Modis Sensor products. To differentiate pixels and identify various phenomena, the acquired images were processed using Geographic Information Systems (GIS) technology. Analysis of seasonal Snow cover changes using Modis Sensor imagery indicates a significant decreasing trend in the majority of the studied area, particularly in the elevated regions. Notably, only the western and southwestern regions of the study area exhibit no discernible decreasing trend. Furthermore, the examination of snow-covered days throughout the study period reveals a decrease in Snow cover in the Middle Zagros, with these changes intensifying in recent years, especially in the snow-covered areas of the region. Changes in Snow cover during the winter months, particularly in elevated areas, were observed to be more pronounced compared to other seasons and regions within the study area.

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