Integrated landslide risk assessment utilizing open source satellite and ground data in the Himalayas of Northern Pakistan

Naseem Ahmad (), Muhammad Shafique (), Mian Luqman Hussain, Munawar Shah (), Punyawi Jamjareegulgarn, Nassir Saad Alarifi () and Mostafa R. Abukhadra ()
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Naseem Ahmad: University of Peshawar
Muhammad Shafique: University of Peshawar
Mian Luqman Hussain: University of Peshawar
Munawar Shah: Tongji University
Punyawi Jamjareegulgarn: King Mongkut’s Institute of Technology Ladkrabang
Nassir Saad Alarifi: College of Science King Saud University
Mostafa R. Abukhadra: Applied Science Private University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2025, vol. 121, issue 13, No 28, 15787 pages

Abstract: Abstract Landslides have devastating effect on communities, infrastructure, and the environment, making them one of the most recurring and harmful natural hazards globally. This study propose an integrated approach of freely available geospatial data and semi-quantitative techniques to evaluate landslide hazard, vulnerability, and risk in one of the most landslide-prone valleys i.e., Kaghan Valley, northern Pakistan. The Google Earth Pro, high-resolution DEM and satellite images are used to develop a landslide inventory, derived causative factors and assess the landslide hazard and risk assessment in Kaghan Valley. The landslide susceptibility map is then integrated with landslide-triggering factors to derive a landslide hazardindex map. A geospatial database of element-at-risk data of 66,282 building footprints, typological data, road network, population, and land cover are obtained through remote sensing and extensive field surveys. The quantitative analysis revealed that 8.43 km2 (0.66%) of the total area falls under the very high-risk category, while 271.19 km2 (21.11%) is classified as high risk, and 80.91 km2 (6.30%) as moderate risk, establishing a strong basis for risk assessment.

Keywords: Hazard; Landslide susceptibility; Risk assessment; Spatial multi-criteria evaluation; Vulnerability (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11069-025-07443-5

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