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An evaluation of landslide susceptibility using probability statistic modeling and GIS's spatial clustering analysis

机译：基于概率统计模型和GIS空间聚类分析的滑坡敏感性评价

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As landslides caused multiple casualties and destructions on a global scale, various models were applied to landslide susceptibility evaluation. In this study, a probability statistic model called the certain factor was adopted to assess the landslide susceptibility of Danba, a county in southwestern China, where the landslide events occur frequently but were poorly understood in regional landslide susceptibility. With the validation of area under the prediction rate curve, the resulting susceptibility map has the accuracies of 0.8211 and 0.8288 in experiment area and verification area, respectively. The validated assessment result was further processed to identify landslide-prone areas with the aid of the spatial clustering analysis of geographic information system. Two clustering indexes including Moran's I statistic and local indicator of spatial association (LISA) were involved. The Moran's I index of 0.959 and the LISA identification result accordant with previous investigations proved that the proposed method was rational and efficient to find the landslide-prone regions and make relevant decisions.
机译：由于滑坡在全球范围内造成了许多人员伤亡和破坏，因此将各种模型应用于滑坡敏感性评估。在这项研究中，采用了被称为“确定因素”的概率统计模型来评估中国西南部县丹坝的滑坡敏感性，该地区滑坡事件频繁发生，但对区域滑坡敏感性的了解却很少。通过预测率曲线下的面积验证，得出的磁化率图在实验区域和验证区域的精度分别为0.8211和0.8288。借助地理信息系统的空间聚类分析，对经过验证的评估结果进行进一步处理，以识别易发生滑坡的区域。涉及两个聚类指标，包括Moran的I统计量和空间关联局部指标（LISA）。 Moran的I指数为0.959，LISA的鉴定结果与以前的研究结果相吻合，证明了该方法是合理有效的，可以找到容易发生滑坡的地区并做出相关决策。

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