Title of article :
Estimating the Impact of Land Cover Change on Soil Erosion Using Remote Sensing and GIS Data by USLE Model and Scenario Design
Author/Authors :
Fu, Anmin Academy of Inventory and Planning - National Forestry and Grassland Administration, China , Cai, Yulin College of Geodesy and Geomatics - Shandong University of Sciences and Technology - Qingdao, China , Sun,Tao Academy of Inventory and Planning - National Forestry and Grassland Administration, China , Li1, Feng Academy of Inventory and Planning - National Forestry and Grassland Administration, China
Pages :
10
From page :
1
To page :
10
Abstract :
Great efforts have been made to curb soil erosion and restore the natural environment to Inner Mongolia in China. The purpose of this study is to evaluate the impact of returning farmland to the forest on soil erosion on a regional scale. Considering that rainfall erosivity also has an important impact on soil erosion, the effect of land use and land cover change (LUCC) on soil erosion was evaluated through scenario construction. Firstly, the universal soil loss equation (USLE) model was used to evaluate the actual soil erosion (2001 and 2010). Secondly, two scenarios (scenario 1 and scenario 2) were constructed by assuming that the land cover and rainfall-runoff erosivity are fixed, respectively, and soil erosion under different scenarios was estimated. Finally, the effect of LUCC on soil erosion was evaluated by comparing the soil erosion under actual situations with the hypothetical scenarios. The results show that both land use/cover change and rainfall-runoff erosivity change have significant effects on soil erosion. The land use and land cover change initiated by the ecological restoration projects have obviously reduced the soil erosion in this area. The results also reveal that the method proposed in this paper is helpful to clarify the influencing factors of soil erosion.
Keywords :
Scenario Design , USLE Model , GIS Data , Remote Sensing , Soil Erosion Using
Journal title :
Scientific Programming
Serial Year :
2021
Full Text URL :
Record number :
2613558
Link To Document :
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