Determination and application of the weights for landslide susceptibility mapping using an artificial neural network
Determination and application of the weights for landslide susceptibility mapping using an artificial neural network
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DOI：
10.1016/s0013-7952(03)00142-x
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发表时间：
2004-02-01
影响因子：
7.4
通讯作者：
Park, HJ
中科院分区：
文献类型：
--
作者：
Lee, S;Ryu, JH;Park, HJ
本研究的目的是开发，应用和评估的概率和人工神经网络方法评估滑坡的敏感性在选定的研究领域。作为基本的分析工具，地理信息系统（GIS）用于空间数据管理和操作。滑坡的位置和滑坡相关的因素，如坡度，曲率，土壤质地，土壤排水，有效厚度，木材类型，木材直径用于分析滑坡的敏感性。采用概率方法计算了各因素类对滑坡发生的相对重要性等级。为确定各因素对滑坡发生的相对重要性的权重，提出了一种人工神经网络方法。使用这些方法，滑坡敏感性指数（LSI）计算使用的评级和权重，并使用该指数产生的滑坡敏感性图。滑坡敏感性分析的结果，有和没有权重，证实了与滑坡位置数据的比较。加权后的比较结果优于不加权的结果。计算出的权重和等级可用于滑坡易发性制图。(C)2003 Elsevier B.V.保留所有权利。
The purpose of this study is the development, application, and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic lnformation System (GIS) was used for spatial data management and manipulation. Landslide locations and landslide-related factors such as slope, curvature, soil texture, soil drainage, effective thickness, wood type, and wood diameter were used for analyzing landslide susceptibility. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence. For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index (LSI) was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping. (C) 2003 Elsevier B.V. All rights reserved.