提出考虑地表土地利用/植被对汇流影响的基于多流向上坡汇流累积的地形因子提取算法,改进了修正通用土壤流失方程(revised university soil loss equation,RUSLE)中地形因子算法,提高了土壤侵蚀提取的精度。利用地理信息系统和遥感技术研究了淮河流域商城县的土壤侵蚀强度空间分布及其与环境因素的关系。结果表明: 研究区年平均土壤侵蚀模数为28.16 t·hm -2·a -1,属于中度侵蚀; 总侵蚀面积达905.95 km 2; 随着坡度的升高,土壤侵蚀强度和侵蚀模数也显著升高。研究为RUSLE模型应用在生态功能区进行土壤侵蚀评估提供了技术范例,为该区域治理水土流失和环境可持续发展提供了依据。
In this paper, a topographic factor extraction algorithm based on the accumulation of the multiple flow direction up-slope considering the effect of land use/vegetation on the confluence is proposed, which improves the topographic factor extraction algorithm in revised university soil loss equation (RUSLE) and improves the accuracy of soil erosion extraction. The spatial distribution of soil erosion intensity and its relationship with environmental factors in Shangcheng County of Huaihe River basin were studied by using geographic information system (GIS) and remote sensing (RS) techniques. The results show that the average annual soil erosion modulus is 28.16 t·hm -2·a -1, suggesting moderate erosion. The total erosion area reaches 905.95 km 2, soil erosion intensity and erosion modulus also increase significantly with the increase of slope. The study provides a technical example for the application of the RUSLE model to soil erosion assessment in the ecological functional region and provides an effective basis for soil erosion control and environmental sustainable development in this region.
李亚平, 卢小平, 张航, 路泽忠, 王舜瑶. 基于GIS和RUSLE的淮河流域土壤侵蚀研究——以信阳市商城县为例[J]. 国土资源遥感, 2019, 31(4): 243-249.
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