LANDSLIDE SUSCEPTIBILITY ASSESSMENT ALONG THE DUBAIR-DUDISHAL SECTION OF THE KARAKORAM HIGWAY, NORTHWESTERN HIMALAYAS, PAKISTAN

The primary objective of this study is to analyze and characterize landslides in North Pakistan along Karakoram Highway (KKH) to produce a landslide susceptibility map using GIS and remote sensing technology. Using satellite images followed by field investigations, spatial distribution of landslide database was generated. Next, an integrated study was undertaken in the study area to perform the landslide susceptibility mapping. Dubaur-Dudishal section of KKH (about 150 km) which is a part of Kohistan Island Arc, is investigated in this study with a buffer zone of about 8 km along both sides of the KKH. Several thematic maps, e.g., lithology, distance to faults, distance to streams, distance to roads, normalized difference vegetation index (NDVI), slope, aspect, elevation, relative relief, plan-curvature and profile-curvature were prepared. Subsequently, these thematic data layers were analyzed by frequency ratio (FR) model and weights-of-evidence (WoE) model to generate the landslide susceptibility maps. In order to check the accuracy of the models, the area under the curve (AUC) was to quantitatively compare the two models used in this study. The predictive ability of AUC values indicate that the success rates of FR model and WoE model are 0.807 and 0.866, whereas the prediction rates are 0.785 and 0.846, respectively. Both methods show that nearly 50 % landslides in the study area fall in either high or very high susceptibility zones. The landslide susceptibility maps presented in this study are of great importance to the policy makers and the engineers for highway construction as well as the mega dams construction projects (Dasu dam and Bhasha dam which lie within the vicinity of the study area); so that proper prevention as well as mitigation could be done in advance to avoid the possible economic as well as the human loss in future.

Automated summary

This study aims to analyze landslides in North Pakistan along Karakoram Highway, mapping landslide susceptibility using GIS and remote sensing technology. Thematic maps were prepared and models were used to generate susceptibility maps with predictive ability indicators. The results show that about 50% of landslides in the study area fall in high or very high susceptibility zones, providing important information for policy makers and engineers.