Published

2026-09-05

Geospatial Assessment of Landslide Susceptibility Mapping in Sheringal DIR, NW Pakistan

Evaluación geoespacial de la cartografía de susceptibilidad a deslizamientos en Sheringal DIR, noroeste de Pakistán

DOI:

https://doi.org/10.15446/esrj.v30n(2).122920

Keywords:

Landslide susceptibility, analytical hierarchy process, Weighted overlay, Geographic Information System (GIS), Pakistan (en)
cartografía de susceptibilidad a deslizamientos (LSM), Proceso de Jerarquía Analítica (AHP), Método de Superposición Ponderada (WOM), SIG (es)

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Authors

  • Waseem ur Rahman Department of Earth Sciences, Quaid-I-Azam University, Islamabad 45320, Pakistan
  • Faisal Rehman Department of Earth Sciences, Quaid-I-Azam University, Islamabad 45320, Pakistan
  • Junaid Khalid Department of Earth Sciences, Quaid-I-Azam University, Islamabad 45320, Pakistan
  • Said Mukhtar Ahmad Chengdu University of Technology https://orcid.org/0000-0002-4666-8343
  • Jamil Siddique Department of Earth Sciences, Quaid-I-Azam University, Islamabad 45320, Pakistan
  • Tahir Azeem Department of Earth Sciences, Quaid-I-Azam University, Islamabad 45320, Pakistan

The Sheringal region of Upper Dir, situated in the tectonically active Kohistan mountains of northern Pakistan, experiences frequent landslides due to steep slopes, monsoon rainfall, and anthropogenic influences. This study addresses the lack of localized susceptibility models by developing and evaluating a decision-support framework for assessing landslide susceptibility in the Sheringal region of northern Pakistan. Eleven causative factors, namely slope, lithology, rainfall, earthquake zones, distance to faults, elevation, NDVI, distance to streams, roads, TWI, and aspect, were weighted using the Analytical Hierarchy Process (AHP) and Weighted Overlay Mapping (WOM) approaches. An inventory of 71 landslides were marked from satellite data and field observations, which guided the calibration of the model results. Results identified slope as the dominant factor, followed by lithology and rainfall. Validation through ROC curves confirmed strong predictive accuracy (AHP AUC: 0.83; WOM AUC: 0.79). Landslide susceptibility maps from both approaches were developed and classified into low to high-risk zones. Both the AHP and WOM susceptibility maps revealed nearly consistent spatial distributions, the AHP model exhibited slightly better predictive capability based on the validation results, indicating that it offers a more precise assessment of landslide susceptibility in the studied region. Theses maps provide valuable information for identifying high risk regions and can support slope stabilization measures and land-use planning.

La región de Sheringal en Dir, situada en las montañas tectónicamente activas de Kohistán en el norte de Pakistán, experimenta deslizamientos frecuentes debido a las pendientes pronunciadas, las lluvias monzónicas y las influencias antropogénicas. Este estudio aborda la falta de modelos de susceptibilidad localizados mediante el desarrollo y la evaluación de un marco de apoyo a la toma de decisiones para la evaluación de la susceptibilidad a deslizamientos en la región de Sheringal, norte de Pakistán. Once factores causales, a saber: pendiente, litología, precipitación, zonas sísmicas, distancia a fallas, elevación, NDVI, distancia a ríos, carreteras, TWI y orientación, fueron ponderados utilizando los enfoques de Proceso de Jerarquía Analítica (AHP) y Mapeo de Superposición Ponderada (WOM). Se registró un inventario de 71 deslizamientos a partir de datos satelitales y observaciones de campo, que sirvieron para calibrar los resultados del modelo. Los resultados identificaron la pendiente como el factor dominante, seguida de la litología y la precipitación. La validación mediante curvas ROC confirmó una alta precisión predictiva (AHP AUC: 0.83; WOM AUC: 0.79). Se elaboraron mapas de susceptibilidad a deslizamientos con ambos enfoques y se clasificaron en zonas de bajo a alto riesgo. Ambos mapas de susceptibilidad (AHP y WOM) mostraron distribuciones espaciales casi consistentes; sin embargo, el modelo AHP presentó una capacidad predictiva ligeramente superior según los resultados de validación, lo que indica que ofrece una evaluación más precisa de la susceptibilidad a deslizamientos en la región estudiada. Estos mapas proporcionan información valiosa para identificar regiones de alto riesgo y pueden apoyar medidas de estabilización de taludes y planificación del uso del suelo.

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How to Cite

ur Rahman, W. ., Rehman, F., Khalid, J., Ahmad, S. M., Siddique, J., & Azeem, T. (2026). Geospatial Assessment of Landslide Susceptibility Mapping in Sheringal DIR, NW Pakistan. Earth Sciences Research Journal, 30((2), 193-203. https://doi.org/10.15446/esrj.v30n(2).122920

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