Landslide Inventory and Landslide Susceptibility Mapping for China Pakistan Economic Corridor (CPEC)’s main route (Karakorum Highway)

Abstract

The landslide inventory helps to develop landslide susceptibility maps which further assist to minimize economic and human losses as well as towards hazard management. This work investigates landslide hazard mapping in the rugged mountain terrain vis-a-vis highly economically significant route between China and Pakistan i.e. Karakuram Highway (KKH). KKH is passing through the Karakorum mountainous region where landslides events occur frequently and prone to serious risk to local travelers, tourists, and to trading caravans. In this work, landslide inventory was developed (302 landslides) along KKH by visual interpretation of Sentinel and google images. Field survey was also carried to validate landslide datasets. Traditional knowledge-based model i.e. Analytic Hierarchy Process (AHP) and data-based models that include Frequency Ratio (FR) and weight of evidence were applied and compared to develop landslide susceptibility maps (LSM). The landslide dataset was divided into modelling/training (70%) and testing/validation (30%) datasets. LSMs are validated by Area Under Curve (AUC) criterion. The results show that weight of evidence, AHP and FR have success rate curves of 61%, 72% and 84%, respectively. In addition, most highly accurate models are validated for their prediction power using testing landslide datasets. The results for prediction capacity for weight of evidence, AHP and FR are 72%, 58%, and 64%, respectively. Further, landslide susceptibility index (LSI) maps are classified into susceptibility zones. The validation and prediction results show that FR model is the most reliable and accurate model for our study area. Our results will be helpful to minimize landslide hazard losses along KKH, ultimately assisting in successful implementation of CPEC idea between China and Pakistan.

SBAS-InSAR based validated landslide susceptibility mapping along the Karakoram Highway: a case study of Gilgit-Baltistan, Pakistan

“…Since the area's active fault and shear zones significantly affect landslide activity (Fig. 7 ) 4 . The most vulnerable formations are the Yasin group and Quaternary alluvium 81 .…”

“…It is the only trade route between the two countries and has become increasingly important to their economies due to the China-Pakistan Economic Corridor (CPEC) initiative. KKH is often called the "Eighth Wonder of the World" (UNESCO 2010) due to its construction in challenging circumstances 4 . Hundreds of rockfalls, rockslides, and debris flow along the KKH have damaged its reputation since it was finished in 1979 5 , 6 .…”

Integrated Spatial Analysis of Forest Fire Susceptibility in the Indian Western Himalayas (IWH) Using Remote Sensing and GIS-Based Fuzzy AHP Approach

“…Remote sensing data and GIS-based analysis offer the advantage of being able to monitor large areas from a distance, providing valuable information on the state of forests and potential threats such as forest fires [86]. The Fuzzy-AHP technique is an effective tool in multi-criteria evaluations and has been found effective for vulnerability assessment in various studies, including [87][88][89][90]. In this investigation, a Fuzzy-AHP model was created and evaluated for assessing vulnerability to forest fires.…”