Soil Degradation Risk Prediction Integrating RUSLE with Geo-information Techniques, the Case of Northern Shaanxi Province in China | Science Publications

American Journal of Applied Sciences

Mushtak T. Jabbar¹  Xiaoling Chen¹ 

关键词: Geoinformation Techniques;    Soil Erosion;    RUSLE;    Shaanxi;    China;   

DOI  :  10.3844/ajassp.2005.550.556

学科分类：自然科学（综合）

来源: Science Publications

【 摘 要 】

This research integrated the Revised Universal Soil Loss Equation (RUSLE) with RS, GISand GPS techniques to quantify soil erosion risk and the northern part of Shaanxi province in Chinawas taken as a case. A system was established for rating soil erodibility, slope length/gradient, rainfallerosivity and conservation practices. The rating values served as inputs into a modified RevisedUniversal Soil Loss Equation (RUSLE) to calculate the risk for soil degradation processes, namely,soil water erosion. Two Landsat TM senses in 1987 and 1999, respectively, were used to produce landuse/ cover maps of the study area based on the maximum likelihood classification method. These mapswere then used to generate the conservation practice factor in the RUSLE. ERmapper and Arc/Infosoftware were used to manage and manipulate thematic data, to process satellite images and tabulardata source. In term of statistic analysis 3985.9 km² (33.12%) of land area had slight to moderate soilerosion risk, 1583.5 km² (13.16%) had moderately high soil erosion risk, 2941.4 km² (24.44%) hadhigh soil erosion risk and 3522.1 km² (29.27%) of the total land area was in a very high soil erosionrisk. The study area, in general, is exposed to high risk of soil water erosion.

【 授权许可】

Unknown