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Regional landslide susceptibility zoning with considering the aggregation of landslide points and the weights of factors

机译:考虑滑坡点聚集和因素权重的区域滑坡敏感性区划

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In this paper, we propose a methodology for landslide susceptibility assessment at a regional scale in Yunnan, southwestern province of China. A landslide inventory map including 3,242 landslide points was prepared for the study area. Five factors recognized as correlated to landslide (namely, lithology, relative relief, tectonic fault density, rainfall, and road density) were analyzed and mapped in geographic information system. An index expressing the correlation between each factor and landslides [called class landslide susceptibility index (CLSI)] was proposed in the study.While analyzing landslide distribution in a large area, point aggregation might be expected. To quantify the uncertainty caused by aggregation, class landslide aggregation index was proposed. To account for the importance of each of the factors in the landslide susceptibility assessment, some weights were calculated by means of analytic hierarchy process. We propose a weighted class landslide susceptibility model (WCLSM), obtained by the combination of CLSI values of each factor with the correspondent weight. WCLSM performance in the study area was evaluated comparing the results obtained by first modeling all landslides and then by performing a time partition. The model was run including only landslides that occurred before 2009 and then validated with respect to landslides that occurred after 2009. The prediction-rate curve shows that the WCLSM model provides a good prediction for the study area. Of the study area, 21.4% shows very high and high susceptibility and includes the 87.7% of the number of landslides that occurred after 2009.
机译:在本文中,我们提出了在中国西南部云南省进行区域规模滑坡敏感性评估的方法。为研究区域准备了包括3,242个滑坡点的滑坡清单图。分析了与滑坡相关的五个因素(即岩性,相对起伏,构造断层密度,降雨和道路密度),并将其绘制在地理信息系统中。该研究提出了一种表达各因子与滑坡之间相关性的指标[称为滑坡敏感性指数(CLSI)]。在分析大面积滑坡分布的同时,可能会出现点聚集现象。为了量化由聚集引起的不确定性,提出了类滑坡聚集指数。为了说明滑坡敏感性评估中每个因素的重要性,通过层次分析法计算了一些权重。我们提出了一个加权类滑坡敏感性模型(WCLSM),该模型是通过将每个因子的CLSI值与相应的权重相结合而获得的。通过首先对所有滑坡进行建模,然后进行时间划分,比较了研究结果对WCLSM的性能进行了评估。运行该模型仅包括2009年之前发生的滑坡,然后针对2009年之后发生的滑坡进行验证。预测率曲线表明WCLSM模型为研究区域提供了良好的预测。在研究区域中,有21.4%的人表现出很高的敏感性,其中包括2009年以后发生的滑坡数量的87.7%。

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