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A GIS-based landslide hazard assessment by multiple regression analysis

机译:多元回归分析的基于GIS的滑坡危害评估

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The occurrence of landslides generally depends on complex interactions among a large number of partially interrelated factors. It is appropriate to use multiple regression analysis for predicting landslides from a given set of independent variables. The procedure of landslide hazard assessment by regression analysis, however, requires evaluation of the spatially varying terrain conditions as well as spatial representation of the landslides. In this paper, the multiple regression analysis was applied to predict landslides in Himi district from independent factors, such as geology, slope-aspect, slope angle, land use and soil with Geographic Information System (GIS). Based on GIS, every factor was classified into several clusters and then the statistical weight of every cluster was assigned for every factor respectively. By the weights of five factors, the linear regression's coefficients of these input factors in landslide area were extracted and assigned to the whole region, and then the susceptibility for the potential landslide was obtained to make the landslide hazard assessment map. Geology and slope-aspect factors are the most important ones. Soil factor is not so notable in this research region, though it may be significant in other regions. At last, the average susceptibilities map for existing landslides was made for the engineers to do control work.
机译:山体滑坡的发生通常取决于大量部分相互关联因子之间的复杂相互作用。使用多元回归分析适用于从给定的一组独立变量预测山体滑坡。然而,回归分析的滑坡危害评估程序需要评估空间变化的地形条件以及山体滑坡的空间表示。在本文中,应用了多元回归分析,从独立因素预测HIMI区的滑坡,如地质信息系统(GIS)的地质学,坡面,坡度,土地利用和土壤。基于GIS,每个因素被分为几个集群,然后分别为每个因素分配每个群集的统计权重。通过五个因素的重量,提取并分配到整个区域的线性回归这些输入因子的系数,然后获得了潜在滑坡的敏感性以使山体滑坡危害评估图。地质和斜坡 - 方面因素是最重要的因素。在该研究区域中,土壤因子不太明显,尽管在其他地区可能是显着的。最后,为工程师进行了控制工作,为现有滑坡的平均敏感性图。

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