GIS-based Multi-Criteria Landslide Hazard Zonation in Cameron Highlands: An AHP Approach for Disaster Resilience

Landslides are among the most frequent and destructive hazards in Malaysia’s highland regions, posing threats to communities, infrastructure, and ecosystems. This study aims to develop a GIS-based Landslide Hazard Zonation (LHZ) map for Cameron Highlands using a Multi-Criteria Decision Analysis (MCDA) approach integrated with the Analytic Hierarchy Process (AHP). Five conditioning factors—slope, aspect, rainfall, land use/land cover (LULC), and Normalized Difference Vegetation Index (NDVI)—were derived from remote sensing and spatial datasets. Each factor was reclassified and weighted through AHP, with a consistency ratio (CR = 0.027 < 0.1) confirming reliable judgments. The weighted overlay produced five hazard classes ranging from very low to very high. Results show that approximately 56% of the study area (365 km²) falls within high to very high hazard zones, while only 7% (46 km²) is categorized as low hazard. The findings highlight that unregulated agriculture, slope cutting, and deforestation significantly influence landslide occurrence. This study demonstrates the potential of integrating GIS and AHP for landslide risk assessment and provides an evidence-based tool to support land use planning, slope management, and disaster resilience strategies in highland environments.

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Publication Details

Journal
Journal of Asian Geography
Published
2025-09-28
DOI
https://doi.org/10.36777/jag2025.4.2.4
Primary Topic
Geochemistry and Geologic Mapping
Type
article
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article

GIS-based Multi-Criteria Landslide Hazard Zonation in Cameron Highlands: An AHP Approach for Disaster Resilience

Journal of Asian Geography
Geochemistry and Geologic Mapping
article

GIS-based Multi-Criteria Landslide Hazard Zonation in Cameron Highlands: An AHP Approach for Disaster Resilience

article en

Abstract

Landslides are among the most frequent and destructive hazards in Malaysia’s highland regions, posing threats to communities, infrastructure, and ecosystems. This study aims to develop a GIS-based Landslide Hazard Zonation (LHZ) map for Cameron Highlands using a Multi-Criteria Decision Analysis (MCDA) approach integrated with the Analytic Hierarchy Process (AHP). Five conditioning factors—slope, aspect, rainfall, land use/land cover (LULC), and Normalized Difference Vegetation Index (NDVI)—were derived from remote sensing and spatial datasets. Each factor was reclassified and weighted through AHP, with a consistency ratio (CR = 0.027 < 0.1) confirming reliable judgments. The weighted overlay produced five hazard classes ranging from very low to very high. Results show that approximately 56% of the study area (365 km²) falls within high to very high hazard zones, while only 7% (46 km²) is categorized as low hazard. The findings highlight that unregulated agriculture, slope cutting, and deforestation significantly influence landslide occurrence. This study demonstrates the potential of integrating GIS and AHP for landslide risk assessment and provides an evidence-based tool to support land use planning, slope management, and disaster resilience strategies in highland environments.

Journal of Asian GeographyVol. 4(2)
Northern University of Malaysia (MY)
Climate action
Openalex Percentile: Top 26%
Geochemistry and Geologic Mapping
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