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- Title
Integrated Approach for Landslide Risk Assessment Using Geoinformation Tools and Field Data in Hindukush Mountain Ranges, Northern Pakistan.
- Authors
Shah, Nisar Ali; Shafique, Muhammad; Ishfaq, Muhammad; Faisal, Kamil; Van der Meijde, Mark
- Abstract
Landslides are one of the most recurring and damaging natural hazards worldwide, with rising impacts on communities, infrastructure, and the environment. Landslide hazard, vulnerability, and risk assessments are critical for landslide mitigation, land use and developmental planning. They are, however, often lacking in complex and data-poor regions. This study proposes an integrated approach to evaluate landslide hazard, vulnerability, and risk using a range of freely available geospatial data and semi-quantitative techniques for one of the most landslide-prone areas in the Hindukush mountain ranges of northern Pakistan. Very high-resolution satellite images and their spectral characteristics are utilized to develop a comprehensive landslide inventory and predisposing factors using bi-variate models to develop a landslide susceptibility map. This is subsequently integrated with landslide-triggering factors to derive a Landslide Hazard Index map. A geospatial database of the element-at-risk data is developed from the acquired remote sensing data and extensive field surveys. It contains the building's footprints, accompanied by typological data, road network, population, and land cover. Subsequently, it is analyzed using a spatial multi-criteria evaluation technique for vulnerability assessment and further applied in a semi-quantitative technique for risk assessment in relative risk classes. The landslide risk assessment map is classified into five classes, i.e., very low (18%), low (39.4%), moderate (26.3%), high (13.3%), and very high (3%). The developed landslide risk index map shall assist in highlighting the landslide risk hotspots and their subsequent mitigation and risk reduction.
- Subjects
PAKISTAN; LANDSLIDES; LANDSLIDE hazard analysis; HAZARD mitigation; REMOTE-sensing images; GEOSPATIAL data; LAND use planning; REMOTE sensing
- Publication
Sustainability (2071-1050), 2023, Vol 15, Issue 4, p3102
- ISSN
2071-1050
- Publication type
Article
- DOI
10.3390/su15043102