首页> 外文期刊>Journal of Remote Sensing & GIS >Landslide Susceptibility Zonation Using Bivariate Models, Around Tehri Reservoir, Uttarakhand, India
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Landslide Susceptibility Zonation Using Bivariate Models, Around Tehri Reservoir, Uttarakhand, India

机译:使用双变量模型进行滑坡敏感性分区,印度北阿坎德邦特里水库

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Uttarakhand, the 27th state of India, is highly susceptible to landslides probably owing to its 86% area in Himalayan terrain. In recent times, however, the landslide incidents have increased leaps and bounds mainly due to unprecedented human interventions in the form of settlements, farming, road construction, myriad of hydroelectricity projects. One such case study is done in the current study around the Tehri Dam reservoir, Uttarakhand, India. Landslide causative factors such as slope, aspect, lithology, geology and geomorphology are derived using remote sensing techniques. Thereafter, two methods, Information Value (IV) and weight of evidence (WofE) model were applied and the output was reclassified into five zones viz. very low, low, moderate, high and very high. The validation of these models was performed using area under curve (AUC) analysis, which shows the accuracy of WofE model was 83% while that of IV model was 81%. Both WofE and IV susceptibility map shows 1.95% area under very high susceptibility zone which mostly covers the area bordering the reservoir hence implementing reservoir rim to be most prone for landslides.
机译:印度第27州北阿坎德邦(Uttarakhand)极易遭受山体滑坡的影响,原因可能是其喜马拉雅山地区的面积占86%。然而,最近,滑坡事件突飞猛进,这主要归因于人类对定居点,农业,道路建设,无数水力发电项目等形式的空前干预。在印度Uttarakhand的Tehri大坝水库附近的当前研究中,进行了一项这样的案例研究。滑坡的成因包括斜坡,坡向,岩性,地质和地貌等,是利用遥感技术得出的。此后,应用了两种方法,即信息价值(IV)和证据权重(WofE)模型,并将输出重新分类为五个区域。非常低,低,中等,高和非常高。这些模型的验证是使用曲线下面积(AUC)分析进行的,这表明WofE模型的准确性为83%,而IV模型的准确性为81%。 WofE和IV磁化率图都显示了在非常高的磁化率区域下的1.95%区域,该区域大体上覆盖了与水库接壤的区域,因此实现了水库边缘最容易发生滑坡。

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