Landslides susceptibility assessment by analytical network process: a case study for Kuttiyadi river basin (Western Ghat
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Landslides susceptibility assessment by analytical network process: a case study for Kuttiyadi river basin (Western Ghats, southern India) T. V. Swetha1 · Girish Gopinath1,2 Received: 21 May 2020 / Accepted: 22 September 2020 © Springer Nature Switzerland AG 2020
Abstract In the case of Western Ghats of Kerala located in southern India, landslides become the most devastating hazard during the monsoon season is mainly because of intense rainfall. The recent landslides struck in the months of June and August 2018 were the worst in the history of the state as the damages to life and property happened were very dangerous. From this evidences, being a landslide-prone area a hazard zonation attempted using the terrain susceptibility concept for highlands of Kuttiyadi river basin is a part of Western Ghats in Kozhikode district with a maximum elevation of 1640 m above MSL. Through landslide susceptibility mapping, the assessment of areas likely to have or probable to landslides in the future identified using geospatial and multi-criteria decision-making (MCDM) tool mix. This work explores the usage of the MCDM tool—analytical network process (ANP)-based decision-making approach to determine the relationship between each landslide conditioning factors and to assign weight effectively. Factor maps of various landslide triggering parameters such as slope, soil, landuse, drainage density, stage of landform, lineament density, geology, and geomorphology were prepared and integrated through geospatial analyses in the GIS platform, and the study area (318 km2) is categorized into four classes of unstable (121 km2), moderately unstable (76 km2), stable to moderately stable (124 km2), high vulnerability (67 km2), and very high vulnerability (74 km2). The result of this work concluded that the application of ANP is an effective tool to weight the factors causing landslides and to generate landslide susceptibility zonation map with maximum accuracy using geospatial technology. The validation of output data with landslide inventory data is satisfying it. Keywords Geospatial · MCDM · ANP · Landslide susceptibility-Western Ghats
1 Introduction Landslides are the most frequent natural disasters around the world, it is mainly due to the expansion of urban and man-made structures into potentially hazardous areas, and damage to infrastructure and human life due to this geohazard is very huge [19]. The downslope movement of materials like rocks or soil occurring on a surface of rupture or weak zone of intense shear strain due to the force of gravity acting on its results in the powerful geohazard is
known as a landslide. Based on the type of the movement, type of material landslides can be classified into several types such as fall, topple, slide, spread, flows, and creep and it can be described as rock falls, debris flow, earth flow, etc. [15]. Several factors can cause a landslide event like heavy rainfall, steepness of the slope, soil erosion, weathering, disturbance in week structural features like joints, bedding plane, etc. Pri
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