The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan
The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan
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DOI：
10.1016/j.geomorph.2004.06.010
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发表时间：
2005-02-01
期刊：
影响因子：
3.9
通讯作者：
Yamagishi, H
中科院分区：
文献类型：
--
作者：
Ayalew, L;Yamagishi, H
作为区域灾害管理的第一步，多元统计分析的逻辑回归的形式被用来制作一个滑坡的易感性图在日本中部的角田弥彦山脉。滑坡敏感性图的编制方法有很多种。在本研究中使用逻辑回归不仅是因为这种方法放松了其他多变量统计方法所需的严格假设，而且还证明了它可以与双变量统计分析（BSA）相结合，以简化对最终获得的模型的解释。在敏感性制图中，使用逻辑回归是为了找到最佳拟合函数来描述滑坡的存在或不存在（因变量）与一组独立参数（如坡度和岩性）之间的关系。在这里，87个滑坡的库存地图被用来产生一个因变量，它采取的值为0的不存在和1的斜坡故障的存在。岩性、基岩-边坡关系、线性构造、坡度、坡向、高程和道路网作为独立参数。每个参数对滑坡发生的影响进行了评估，从相应的系数，出现在逻辑回归函数。对系数的解释表明，道路网络在决定滑坡的发生和分布方面发挥着重要作用。在地貌参数，方面和坡度比海拔有更显着的贡献，虽然实地观察表明，后者是一个很好的估计的大致位置的边坡切割。利用概率预测图，将研究区划分为极低、极低、低、中、高5类滑坡易发性。中、高磁化率区占总研究面积的8.87%，主要分布在卡库达山东部和弥彦山中部和南部的中海拔斜坡上。(C)2004 Elsevier B.V保留所有权利。
As a first step forward in regional hazard management, multivariate statistical analysis in the form of logistic regression was used to produce a landslide susceptibility map in the Kakuda-Yahiko Mountains of Central Japan. There are different methods to prepare landslide susceptibility maps. The use of logistic regression in this study stemmed not only from the fact that this approach relaxes the strict assumptions required by other multivariate statistical methods, but also to demonstrate that it can be combined with bivariate statistical analyses (BSA) to simplify the interpretation of the model obtained at the end. In susceptibility mapping, the use of logistic regression is to find the best fitting function to describe the relationship between the presence or absence of landslides (dependent variable) and a set of independent parameters such as slope angle and lithology. Here, an inventory map of 87 landslides was used to produce a dependent variable, which takes a value of 0 for the absence and 1 for the presence of slope failures. Lithology, bed rock-slope relationship, lineaments, slope gradient, aspect, elevation and road network were taken as independent parameters. The effect of each parameter on landslide occurrence was assessed from the corresponding coefficient that appears in the logistic regression function. The interpretations of the coefficients showed that road network plays a major role in determining landslide occurrence and distribution. Among the geomorphological parameters, aspect and slope gradient have a more significant contribution than elevation, although field observations showed that the latter is a good estimator of the approximate location of slope cuts. Using a predicted map of probability, the study area was classified into five categories of landslide susceptibility: extremely low, very low, low, medium and high. The medium and high susceptibility zones make up 8.87% of the total study area and involve mid-attitude slopes in the eastern part of Kakuda Mountain and the central and southern parts of Yahiko Mountain. (C) 2004 Elsevier B.V All rights reserved.