Evaluating Ecological Degradation of Kosalan Protected Area using Remote Sensing and GIS

Document Type : Research Article

Authors

• Zahra Jalilian ¹
• Jamil Amanollahi ²

¹ MSc in Environmental Sciences, Department of Environmental Sciences, Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran

² Associate Professor, Department of Environmental Sciences, Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran

10.22067/geoeh.2022.75467.1184

Abstract

Protected areas are defined as a pattern of land use in the environmental planning process. However, they are excluded from any physical exploitation or their use is conditional. They are no less important than other lands. This study aimed to evaluate the ecological degradation of Kosalan protected area using remote sensing and GIS techniques. Images of two time periods 1989 and 2020 were prepared. For this purpose, after radiometric and atmospheric corrections of NDVI index, changes of vegetation in the region in the two time periods were evaluated. Then, to model the ecological degradation, eight criteria including distance from the village, distance from the road, landslide points, erosion intensity, slope, direction, altitude and vegetation were used. The criteria were weighted by hierarchical analysis process method and standardized by fuzzy model. Vegetation changes at different thresholds were analyzed. According to the vegetation situation in the region, 3 thresholds of 0.1-3, 0.1-1 and 0.1-1 were used. The results of this evaluation showed that the quality and density of vegetation has decreased a lot during 31 years. The results of ecological degradation modeling showed that the most effective criterion in causing degradation is distance from the village. In general, 50% of the area has a high potential for ecological degradation. The results showed that the greatest potential for ecological degradation was in the central areas of the southeast and center of the region, where the slope and altitude are high. The impact of slope is so high in these places.

Graphical Abstract

Keywords

• AHP
• NDVI
• Fuzzy
• Modeling
• Vegetation Density

20.1001.1.23221682.1402.12.1.3.2

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