Application of AHP based geospatial modeling for assessment of landslide hazard zonation along Mughal road in the Pir Panjal Himalayas

Mughal road located in the high mountainous region of Kashmir Himalaya, India is prone to landslide hazards because of anthropogenic pressure and ongoing climate change. Landslides along the roads is one of the critical problems in hilly areas. Landslide vulnerability maps can serve as an effective tool for the planning and management of landslide disasters. The primary goal of the present study is to generate a Landslide hazard map along the Mughal Road. An integrated approach of Remote sensing GIS and AHP was used applied for this purpose. The eight most important landslide occurrence parameters including slope aspect, geology, elevation, slope angle, lineament buffer, drainage buffer, landuse/landcover and NDVI were employed in the present model. The Advanced Spaceborne Thermal Emission and Reflection Radiometer Digital Elevation Model and Linear Imaging Self-Scanning Sensor imagery were used to prepare these thematic layers in Arc GIS environment. The analysis of the final landslide hazard map reveals that, very low, low and moderate landslide hazard zones constitute 0.6%, 15.8% and 41.3% of the total area in the study region, respectively. While High and very high landslide hazard zones account for 30.2% and 12.2%, respectively of the total geographical area in the study region. Finally, an inventory of landslides has been used to validate the findings of the study. The landslide hazard zonation map has been also compared with the Landslide inventory map through the ROC-AOC method. The applied model produced an excellent result for landslide hazard mapping in the research region, as shown by the spatial effectiveness of the generated landslide hazard map validated by AUC (77.7% of accuracy). The study can be very useful for policy maker and construction planners.

Automated summary

To address landslide hazards in the Mughal road area of Kashmir Himalaya, researchers used remote sensing and GIS techniques to create a landslide hazard map. The map divides the region into very low, low, moderate, high, and very high landslide hazard zones, providing valuable information for decision makers and planners.