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<p>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 km<sup>2</sup> (0.66%) of the total area falls under the very high-risk category, while 271.19&#xa0;km<sup>2</sup> (21.11%) is classified as high risk, and 80.91&#xa0;km<sup>2</sup> (6.30%) as moderate risk, establishing a strong basis for risk assessment.</p>

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

  • 期刊论文

  • 发表日期：

    2025年7月1日

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  • Naseem Ahmad,
  • Muhammad Shafique,
  • Mian Luqman Hussain,
  • Munawar Shah,
  • Punyawi Jamjareegulgarn,
  • Nassir Saad Alarifi,
  • Mostafa R. Abukhadra

摘要

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.