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A GIS-based factor clustering and landslide susceptibility analysis using AHP for Gish River Basin, India

机译:基于GIS的因子聚类和利用AHP对印度Gish River河流域的滑坡敏感性分析

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Landslide susceptibility map provides a useful tool to the decision-makers to prevent and mitigate landslide hazards. For this study 16 spatial parameters and past landslide inventory have been taken into consideration and these are categorized under six factors clusters. For providing relative importance to the parameters modified analytic hierarchy process is taken into consideration. Landslide susceptible zone (LSZ) is prepared compositing all those multiparametric spatial data layers. The obtained result shows that 7.80% area of total basin is highly susceptible for landslide. Correlation and regression analysis suggests that lithological factors cluster is the dominant one for determining very high LSZ. The validation shows that very high LSZ is associated with very high landslide frequency density. Besides this, receiver operating characteristics curve also shows 90.20% predicted area under the curve. So, this model can be treated as valid.
机译:Landslide易感性图为决策者提供了一种有用的工具,以防止和缓解滑坡危险。对于本研究,已考虑16个空间参数和过去滑坡库存,这些参数在六个因素集群下进行分类。为了提供对参数的相对重要性,考虑了修改的分析层次结构。制备山体滑坡易感区(LSZ),编写了所有这些多游艇空间数据层。得到的结果表明,总盆的7.80%面积高易感滑坡。相关性和回归分析表明,岩性因素集群是用于确定非常高的LSZ的主导。验证表明,非常高的LSZ与非常高的滑坡频率密度相关联。除此之外,接收器操作特性曲线还显示了曲线下的90.20%的预测区域。因此,该模型可以视为有效。

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