Geospatial assessment of landslide susceptibility in Astor District, Northern Pakistan

Northern Pakistan is a rough, mountainous region with high gradients, disintegrated lithology, glaciers on the highest peaks, and a seismically active area. District Astor is among the most susceptible locations, with yearly landslides due to various causes. This research has developed a comprehensive landslide inventory and a susceptibility model for the chosen region. Frequency Ratio is the most generally utilized probabilistic method; a moderately Analytical Hierarchy Process (AHP). The Frequency Ratio (FR) model technique has been used to ascertain the connection between both variables that cause landslides and landslides that have been mapped. A persistent Scattered Interferometry Radar (InSAR) technique was employed to investigate deformation movement in the vulnerable zones of the extracted models, finding a high Line-of-Sight (LOS) displacement velocity in both models' extremely sensitive areas. The derived Landslide Susceptibility Index (LSI) models had a prediction accuracy of 84.4% and 78.0% for the FR and AHP methods, respectively, calculated by applying the Area Under Curve (AUC) derived from the Receiver Operating Characteristic (ROC) approach. Finally, five susceptibility classes were assigned to both Landslide hazard index maps. Because the research region is prone to landslides, these susceptible models will be useful in delineating hazardous zones for future landslide catastrophes and utilized in decision-makers' planning strategies for Development initiatives in the studied region.

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Publication Details

Journal
Journal of Degraded and Mining Lands Management
Published
2025-06-30
DOI
https://doi.org/10.15243/jdmlm.2025.124.8083
Citations
1
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
2.42

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article

Geospatial assessment of landslide susceptibility in Astor District, Northern Pakistan

Ritha Nyirandayisabye, Guisheng Hu, Ningsheng Chen, Mir Mujtaba Laghari et al.
1 citations
Journal of Degraded and Mining Lands Management
Landslides and related hazards
2.42
article

Geospatial assessment of landslide susceptibility in Astor District, Northern Pakistan

Ritha Nyirandayisabye, Guisheng Hu, Ningsheng Chen, Mir Mujtaba Laghari, Surih Sibaghatullah Jagirani, Irshad Ali Zardari, Azhar Ali Zardari
article en
1 citations

Abstract

Northern Pakistan is a rough, mountainous region with high gradients, disintegrated lithology, glaciers on the highest peaks, and a seismically active area. District Astor is among the most susceptible locations, with yearly landslides due to various causes. This research has developed a comprehensive landslide inventory and a susceptibility model for the chosen region. Frequency Ratio is the most generally utilized probabilistic method; a moderately Analytical Hierarchy Process (AHP). The Frequency Ratio (FR) model technique has been used to ascertain the connection between both variables that cause landslides and landslides that have been mapped. A persistent Scattered Interferometry Radar (InSAR) technique was employed to investigate deformation movement in the vulnerable zones of the extracted models, finding a high Line-of-Sight (LOS) displacement velocity in both models' extremely sensitive areas. The derived Landslide Susceptibility Index (LSI) models had a prediction accuracy of 84.4% and 78.0% for the FR and AHP methods, respectively, calculated by applying the Area Under Curve (AUC) derived from the Receiver Operating Characteristic (ROC) approach. Finally, five susceptibility classes were assigned to both Landslide hazard index maps. Because the research region is prone to landslides, these susceptible models will be useful in delineating hazardous zones for future landslide catastrophes and utilized in decision-makers' planning strategies for Development initiatives in the studied region.

Journal of Degraded and Mining Lands ManagementVol. 12(4)
Yangtze University (CN), Chinese Academy of Sciences (CN), International Center for Chemical and Biological Sciences (PK), Institute of Mountain Hazards and Environment (CN), University of Chinese Academy of Sciences (CN), Quaid-e-Awam University of Engineering, Science and Technology (PK)
U.S. Geological Survey
Openalex Percentile: Top 11%
Landslides and related hazards
2.42
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