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首页> 外文期刊>American journal of applied sciences >Soil Degradation Risk Prediction Integrating RUSLE with Geo-information Techniques, the Case of Northern Shaanxi Province in China | Science Publications
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Soil Degradation Risk Prediction Integrating RUSLE with Geo-information Techniques, the Case of Northern Shaanxi Province in China | Science Publications

机译:RUSLE与地理信息技术相结合的土壤退化风险预测-以陕北地区为例科学出版物

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> This research integrated the Revised Universal Soil Loss Equation (RUSLE) with RS, GIS and GPS techniques to quantify soil erosion risk and the northern part of Shaanxi province in China was taken as a case. A system was established for rating soil erodibility, slope length/gradient, rainfall erosivity and conservation practices. The rating values served as inputs into a modified Revised Universal 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 land use/ cover maps of the study area based on the maximum likelihood classification method. These maps were then used to generate the conservation practice factor in the RUSLE. ERmapper and Arc/Info software were used to manage and manipulate thematic data, to process satellite images and tabular data source. In term of statistic analysis 3985.9 km2 (33.12%) of land area had slight to moderate soil erosion risk, 1583.5 km2 (13.16%) had moderately high soil erosion risk, 2941.4 km2 (24.44%) had high soil erosion risk and 3522.1 km2 (29.27%) of the total land area was in a very high soil erosion risk. The study area, in general, is exposed to high risk of soil water erosion.
机译: >该研究将修订后的通用土壤流失方程(RUSLE)与RS,GIS和GPS技术相结合,以量化土壤侵蚀风险,并以中国陕西省北部为例。建立了一个用于评估土壤侵蚀性,坡度/坡度,降雨侵蚀力和保护措施的系统。额定值用作修改后的修订的通用土壤流失方程(RUSLE)的输入,以计算土壤退化过程的风险,即土壤水蚀。基于最大似然分类法,分别使用1987年和1999年的两种Landsat TM感测来生成研究区域的土地利用/覆盖图。然后将这些图用于在RUSLE中生成保护实践因子。 ERmapper和Arc / Info软件用于管理和处理主题数据,以处理卫星图像和表格数据源。从统计分析的角度来看,3985.9 km 2 的土地面积有轻度至中度土壤侵蚀风险,1583.5 km 2 的土地面积有中度高土壤侵蚀风险其中,有2941.4 km 2 (24.44%)具有较高的土壤侵蚀风险,而总土地面积中有3522.1 km 2 (29.27%)具有较高的土壤侵蚀风险。研究区域通常面临水土流失的高风险。

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