A GIS-based evaluation on sensitivity of soil erosion in yishusi river watershed

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Abstract

Soil erosion sensitivity is limited by a number of factors, including precipitation, relief, soil quality, vegetation and human activity. With reference to domestic and international work on the assessment of sensitivity to soil erosion and to the natural environment characteristics of Yishusi River watershed, the primary influences on and sensitivity grades of soil erosion are determined. The Soil erodibility factor and vegetation factor values used for soil erosion sensitivity evaluation are obtained by interpreting Landsat TM image data, the rainfall erosion force factor map and slop map are obtained by Digitizing and space analyzes in GIS; We evaluated the factors controlling sensitivity to soil erosion and classified areas according to sensitivity by analyzing the reasons for erosion by GIS. The space distributing of all classificatory soil erosion sensitivity evaluation of Yishusi River watershed is analysized. The results showed that 15.74 percent of the total land(approximately 4987.88km2) are maintaining at high or extremity sensitivity, 53.12 percent of the total land(approximately 16836.39km2) are maintaining at moderate sensitivity,31.14 percent of the total land(approximately 9870.88km2) are maintaining at mild or none sensitivity; it concludes that entire soil erosion sensitivity of Yishusi River watershed is high. At last, this article gives some suggestions and measures for the worse situation. This article is able to support the practice work of soil erosion prevention, monitoring management as well as the land use in watershed. Meanwhile, the development of the index system can also benefit the theory of watershed planning and management. © 2008 Springer Berlin Heidelberg.

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APA

Yan, J., Du, J., Xue, C., & Yang, Q. (2008). A GIS-based evaluation on sensitivity of soil erosion in yishusi river watershed. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5370 LNCS, pp. 591–598). https://doi.org/10.1007/978-3-540-92137-0_65

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