Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.
CSIR-Central Building Research Institute, Roorkee, 247667, India.
Environ Monit Assess. 2022 Mar 1;194(3):234. doi: 10.1007/s10661-022-09851-7.
Landslides are one the most destructive and life-endangering hazard in the Darjeeling Himalayan region and keeping in mind the interest of society and their future prospects identification of landslide potential areas is a very pertinent task in this area. Therefore, the present study aimed toward the landslide susceptibility zonation (LSZ) mapping in and around the Kalimpong region by applying Analytic Hierarchy Process (AHP) method integrated with fifteen causative factors including slope, lineament, drainage density, land use land cover, relative relief, soil texture, lithology, elevation, aspect, thrust and faults, plan curvature, profile curvature, road network, topographic wetness index and stream power index. Tolerance and variance inflation factors with Pearson's correlation coefficient are used to assess potential collinearity among the selected factors, and subsequently, the final model has been constructed by enduring an acceptable consistency ratio (<0.10). Thereafter, to classify this region into very low, low, moderate, high and very high susceptible zones quantile, geometric interval, Jenk's natural break and success rate curve (SRC) techniques are adopted to compare and check the optimum LSZ categorization. Considering the identified 647 landslides, Area Under Curve (AUC) of Receiver Operating Characteristic (ROC) curve is used to gauge the best LSZ map. The AUC ROC shows SRC method (m = 0.9) yields the highest result, achieving a prediction accuracy of 79.5% and, therefore, is considered the most promising LSZ form for the present study area. The results obtained from the study highlight the spatial information of areas that may face slope instability and helps government agencies, stakeholders for drafting adequate measures due to absence of proper landslide early warning systems in this region.
山体滑坡是导致达吉岭喜马拉雅地区破坏和生命威胁的最主要原因之一。考虑到社会利益和他们的未来前景，识别滑坡潜在区域是该地区非常重要的任务。因此，本研究旨在通过应用层次分析法（AHP）方法，结合包括坡度、线性、排水密度、土地利用/土地覆盖、相对海拔、土壤质地、岩性、海拔、方位、逆冲和断层、平面曲率、剖面曲率、道路网络、地形湿度指数和水流功率指数在内的 15 个诱发因素，对 Kalimpong 地区及其周边地区进行滑坡易发性分区（LSZ）制图。采用容忍度和方差膨胀因子以及皮尔逊相关系数来评估所选因素之间的潜在共线性，随后通过忍受可接受的一致性比率（<0.10）来构建最终模型。此后，为了将该地区分为极低、低、中、高和极高易发性区域，采用分位数、几何间隔、Jenks 自然断点和成功率曲线（SRC）技术进行比较和检查最优 LSZ 分类。考虑到确定的 647 个滑坡，使用接收者操作特征（ROC）曲线下的面积（AUC）来衡量最佳 LSZ 图。ROC AUC 表明 SRC 方法（m=0.9）产生了最高的结果，达到了 79.5%的预测准确性，因此被认为是本研究区最有前途的 LSZ 形式。研究结果突出了可能面临边坡不稳定的区域的空间信息，并有助于政府机构和利益相关者制定适当的措施，因为该地区缺乏适当的滑坡预警系统。
