Land Slide Susceptibility Mapping And Modelling, Utilizing Remote Sensing And Gis Data: A Case Study Along The Karakoram Highway (KKH), Gilgit Area, Pakistan

Abstract

Identification of potential landslide zones along KKH (CPEC). The study area starts from Jaglot geographically lies between a latitude of 35ᵒ76′977″ N and a longitude of 74ᵒ57′402″ E to Khunjarab. This study is significant to minimize accidents, economic loss as well as loss of infrastructure. This study is essential for landslide events that occur oftentimes and cause risk to local travelers, tourists, and trading. These study landslide potential zones developed using Google Earth Pro (170) potential zones were identified with the comparison of Google Earth different year satellite images and to develop Road Networks. For Land Use Land Cover (LULC) we use satellite imagery from Alaska Satellite Facility (ASF) sentinel-2 image of 10m resolution for unsupervised classification. We get Digital Elevation Model (DEM) data from USGS 30m resolution to generate flow accumulation, Slope, Aspect, and Network to Stream. From a geological map of the study area, we develop Lithology. We use the Gridded precipitation website to get Meteorological data and develop graphs. After processing of data, we use PS-InSAR Interferometric Synthetic Aperture Radar. (InSAR) for monitoring and processing landslides with high accuracy to identify potential landslide zones. To reduce the degree of uncertainty in results different approaches are used one of them is the Analytical Hierarchy Process (AHP). This shows better results in Land Surface Modeling (LSM) we use this approach to improve accuracy. The results of our study are the potential landslide zones, it’s a probability of damage to the road and human life. The results of our study are potential zones and their high degree of chance to damage infrastructure and lives.