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RS-GIS based morphometrical and geological multi-criteria approach to the landslide susceptibility mapping in Gish River Basin, West Bengal, India

机译:基于RS-GIS基于LISH River河流域Landslide易感性映射的地质多标准方法,印度西孟加拉邦

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Darjeeling Himalaya is one of the several mountainous areas of India which is often suffered from landslide hazards. In this paper, a multi criteria evaluation is applied using 16 morphometric indicators, geology and lineaments to identify the areas vulnerable in respect to drainage and relief conditions. As both drainage and relief parameters exert strong influences on landslide intensity, both the diversity maps are integrated for final landslide susceptibility mapping. The obtained results show that 20.17 sq. km (7.61%) area within the basin is highly susceptible for landslides, where average drainage density is 3.78 km/sq. km , relative relief is greater than 408 m and slope is greater than 12 degrees. The validation result shows that very high landslide susceptible zone is associated with very high frequency of landslide occurrence. Beside this, ROC curve also suggests good predicted rate (86.60%) for the model. So, the proposed method can be applied for predicting landslide susceptible zone. (C) 2018 COSPAR. Published by Elsevier Ltd. All rights reserved.
机译:Darjeeling Himalaya是印度的几个山区之一,通常遭受滑坡危险。在本文中,使用16个形态学指标,地质和谱系来施加多标准评估,以确定易受引流和救济条件易受伤害的区域。随着排水和浮雕参数的影响力强度对滑坡强度的影响力强,各种各样的地图都集成了最终滑坡敏感性映射。所获得的结果表明,盆内的20.17平方公里(7.61%)面积高易感山体滑坡,其中平均引流密度为3.78 km / sq。 KM,相对浮雕大于408米,斜率大于12度。验证结果表明,非常高的滑坡易感区与极高的滑坡发生频率相关。除此之外,ROC曲线还表明了该模型的良好预测率(86.60%)。因此,所提出的方法可以应用于预测滑坡易感区。 (c)2018 Cospar。 elsevier有限公司出版。保留所有权利。

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