INTEGRATING GIS AND REMOTE SENSING TO ASSESS THE RISK OF LANDSLIDE IN NKHULAMBE COMMUNITY, PHALOMBE
Abstract
Landslides pose a major threat to communities in mountainous regions, especially in developing countries like Malawi, where disaster risk management is hindered by weak institutional capacity and limited data. The Nkhulambe Community in Phalombe District, affected by events like Cyclone Freddy in 2023, was the focus of this study, which used GIS and remote sensing to assess landslide risk and support local and national disaster preparedness.
The research integrated Sentinel-2A satellite imagery, SRTM DEM data, and socio-economic surveys to evaluate landslide susceptibility using the Information Value Method (IVM). Nine factors slope, elevation, aspect, soil depth, land use, rainfall, distance to streams, landform and lithology were analyzed. The susceptibility map showed that central and northern areas faced very high risk due to steep slopes, sedimentary rock type, proximity to river banks, and high rainfall. Physical vulnerability was assessed by mapping infrastructure and agricultural land, with high-risk zones overlapping susceptibility areas, particularly around villages like Nachuma, Nagoli A, and Nititha. Social surveys revealed strong awareness of landslide risks but poor preparedness: only 12% had access to early warning systems, and 76% did not know how to respond during an event.
A final landslide risk map combined susceptibility and vulnerability layers, identifying zones of varying risk levels. This tool supports land-use planning and emergency response strategies. Key recommendations include integrating GIS-based maps into local planning, strengthening early warning systems, improving meteorological collaboration, and launching education campaigns to boost community resilience. This study contributes to GIS-based landslide risk assessment in data-limited settings and aligns with global frameworks like the Sendai Framework and SDG 11, offering a replicable model for disaster risk management across Malawi and similar contexts.
Research summary
Landslides pose a major threat to communities in mountainous regions, especially in developing countries like Malawi, where disaster risk management is hindered by weak institutional capacity and limited data. The Nkhulambe Community in Phalombe District, affected by events like Cyclone Freddy in 2023, was the focus of this study, which used GIS and remote sensing to assess landslide risk and support local and national disaster preparedness. Social surveys revealed strong awareness of landslide risks but poor preparedness: only 12% had access to early warning systems, and 76% did not know how to respond during an event. This study contributes to GIS-based landslide risk assessment in data-limited settings and aligns with global frameworks like the Sendai Framework and SDG 11, offering a replicable model for disaster risk management across Malawi and similar contexts.