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首页> 外文期刊>Bulletin of engineering geology and the environment >A comparative assessment of information value, frequency ratio and analytical hierarchy process models for landslide susceptibility mapping of a Himalayan watershed, India
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A comparative assessment of information value, frequency ratio and analytical hierarchy process models for landslide susceptibility mapping of a Himalayan watershed, India

机译：印度喜马拉雅流域滑坡敏感性图的信息价值，频率比和层次分析模型的比较评估

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摘要

This research work presents a comparative performance of geographic information system (GIS)-based statistical models for landslide susceptibility mapping (LSM) of the Himalayan watershed in India. A total of 190 landslide locations covering an area of 14.63km(2) were identified in the watershed, using high-resolution linear imaging self-scanning (LISS IV) data. The causative factors used for LSM of the study area are slope, aspect, lithology, curvature, lineament density, land cover and drainage buffer. The spatial database has been prepared using remote sensing data along with ancillary data like geological maps. LSMs were prepared using information value (InV), frequency ratio (FR) and analytical hierarchy process (AHP) models. The validation results using the prediction rate curve technique show 89.61%, 87.12% and 88.26% area under curve values for FR, AHP and InV models, respectively. Therefore, the frequency ratio (FR) model could be used for LSM in other parts of this hilly terrain.
机译：这项研究工作提出了一种基于地理信息系统（GIS）的印度喜马拉雅流域滑坡敏感性地图（LSM）统计模型的比较性能。使用高分辨率线性成像自扫描（LISS IV）数据，在该流域中总共确定了190个滑坡位置，面积14.63km（2）。用于研究区域的LSM的成因包括坡度，纵横比，岩性，曲率，线面密度，土地覆盖率和排水缓冲区。已使用遥感数据以及诸如地质图之类的辅助数据来准备空间数据库。使用信息值（InV），频率比（FR）和层次分析法（AHP）模型来准备LSM。使用预测率曲线技术的验证结果显示，对于FR，AHP和InV模型，曲线下面积分别为89.61％，87.12％和88.26％。因此，频率比（FR）模型可用于该丘陵地带其他部分的LSM。

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