摘要
Every year during the rainy season, water-induced soil erosion poses serious spatial-environmental problems, causing heavy damage to agricultural lands, sedimentation in reservoirs, and water quality problems in nearby surface water bodies, from the plains to the mountain areas in Nepal. The goal of this study is to identify potential areas for soil erosion in sub and macro watershed in Mustang, Nepal using remote sensing (RS) and geographic information systems (GIS) techniques. The study examines the possibility of advanced mapping of soil erosion-prone areas using a high spatial resolution image of QuickBird satellite and medium spatial resolution of Landsat satellite. The satellite image was classified using object-based image analysis (OBIA) techniques, taking into account spectral, spatial, and context information as well as hierarchical properties. The resulting land cover classification was thereafter combined with additional data in ArcGIS, where the input layers were reclassified and all classes of the input layers were ranked according to their proneness to soil erosion. Soil erosion-prone areas were delineated in five classes ranging from “very high” to “very low”. Using high spatial resolution image the study revealed that 22% area categorized as “high erosion-prone” areas and 5% as “very high” or “extremely erosion-prone”. Using medium resolution image the study exposed that 27% area categorized as “high erosion-prone” areas and 6% as “very high” or “extremely erosion-prone”. Comparison between two analysed erosion results almost all the erosion zone area was very close excluding medium erosion-prone category. The study proved GIS modeling techniques can successfully identify soil erosion-prone areas. The soil erosion-prone map produced out of the exercise can be used in decision making, particularly in selecting conservation measures to reduce soil loss.
Every year during the rainy season, water-induced soil erosion poses serious spatial-environmental problems, causing heavy damage to agricultural lands, sedimentation in reservoirs, and water quality problems in nearby surface water bodies, from the plains to the mountain areas in Nepal. The goal of this study is to identify potential areas for soil erosion in sub and macro watershed in Mustang, Nepal using remote sensing (RS) and geographic information systems (GIS) techniques. The study examines the possibility of advanced mapping of soil erosion-prone areas using a high spatial resolution image of QuickBird satellite and medium spatial resolution of Landsat satellite. The satellite image was classified using object-based image analysis (OBIA) techniques, taking into account spectral, spatial, and context information as well as hierarchical properties. The resulting land cover classification was thereafter combined with additional data in ArcGIS, where the input layers were reclassified and all classes of the input layers were ranked according to their proneness to soil erosion. Soil erosion-prone areas were delineated in five classes ranging from “very high” to “very low”. Using high spatial resolution image the study revealed that 22% area categorized as “high erosion-prone” areas and 5% as “very high” or “extremely erosion-prone”. Using medium resolution image the study exposed that 27% area categorized as “high erosion-prone” areas and 6% as “very high” or “extremely erosion-prone”. Comparison between two analysed erosion results almost all the erosion zone area was very close excluding medium erosion-prone category. The study proved GIS modeling techniques can successfully identify soil erosion-prone areas. The soil erosion-prone map produced out of the exercise can be used in decision making, particularly in selecting conservation measures to reduce soil loss.
