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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：喜马拉雅水域滑坡易感性映射信息价值，频率比和分析层次流程模型的比较评估

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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：本研究工作提出了地理信息系统（GIS）的比较表现 - 基于印度喜马拉雅流域的滑坡敏感性映射（LSM）的统计模型。使用高分辨率线性成像自扫描（Liss IV）数据，在流域中识别出面积为14.63km（2）的190个山体滑坡位置。用于研究区域的LSM的致病因素是斜坡，方面，岩性，曲率，裂缝密度，陆盖和排水缓冲液。空间数据库已经使用远程感测数据以及像地质图这样的辅助数据。使用信息值（INV），频率比（FR）和分析层次结构（AHP）模型来编制LSM。使用预测率曲线技术的验证结果分别显示了FR，AHP和INV模型的曲线值下的89.61％，87.12％和88.26％的面积。因此，频率比（FR）模型可用于该丘陵地形的其他部分中的LSM。

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