Landslide susceptibility mapping along the China Pakistan Economic Corridor (CPEC) route using multi-criteria decision-making method

• Published in: Modeling earth systems and environment 2022-06, Vol.8 (2), p.1519-1533
• Main Authors: Maqsoom, Ahsen, Aslam, Bilal, Khalil, Umer, Kazmi, Zaheer Abbas, Azam, Sheheryar, Mehmood, Tahir, Nawaz, Ahsan
• Format: Article
• Language: English
• Subjects: Analytic hierarchy process; Chemistry and Earth Sciences; Computer Science; Decision analysis; Decision making; Earth and Environmental Science; Earth Sciences; Earth System Sciences; Economics; Ecosystems; Environment; Geographic information systems; Geographical information systems; Geological mapping; Hydrology; Information systems; Landslides; Landslides & mudslides; Math. Appl. in Environmental Science; Mathematical analysis; Mathematical Applications in the Physical Sciences; Multiple criterion; Parameter identification; Physics; Remote sensing; Review Article; Statistics for Engineering; Susceptibility
• ISSN: 2363-6203; 2363-6211
• DOI: 10.1007/s40808-021-01226-0

This study maps the landslide susceptibility along the China–Pakistan Economic Corridor (CPEC) route using multiple landslide causative factors. A decisive statistical approach and the Geographic Information System (GIS) were used to map the route’s susceptibility. The study area comprises a 236 km section of the Karakoram Highway, located in a region subjected to repeated landslides. The maps of different causative factors, including topographical, geological, and hydrological factors, were generated through GIS using data obtained from various sources. The causative factors were weighted according to their potential for developing a landslide event in a pairwise matrix of a multi-criteria decision-making approach. The analytical hierarchy process was applied to get the Consistency Index that governed the whole rating process. The weights of the landslide causative factors were used for generating the study area’s final landslide susceptibility map. The results indicated that about 38% of the study area falls under the category of high and very high susceptibility. The outcomes of this study could be valuable in the identification of the parameters at a given area or region that are more prominently influencing the happening of landslides, in this way permitting the more viable preventive measures to be taken.