Open-Source GIS Applications for Flood and Landslide Assessment: Comparative Cases from Poland and Malaysia
DOI:
https://doi.org/10.36777/jag2026.5.2.6Keywords:
Geographic Information Systems, Copernicus, QGIS, flood mapping, landslide analysisAbstract
Research on natural disasters requires analytical procedures that are rapid, reproducible, and based on sound scientific principles. Such procedures should also be accessible to institutions responsible for environmental monitoring, land-use planning, and disaster risk reduction. This study evaluated the practical use of publicly available geospatial data and open-source GIS tools for the preliminary assessment of two contrasting natural hazards: the September 2024 flood in Lower Silesia, Poland, with particular focus on the urban floodplain of Wrocław, and the December 2022 landslide in Batang Kali, Selangor, Malaysia. The study utilised Copernicus Sentinel-2 MSI Level-2A satellite imagery, digital elevation model (DEM) data from the Copernicus programme, OpenStreetMap vector layers, and spatial processing in QGIS. The methodology employed a pre- and post-event change-detection approach based on spectral indices. The Normalized Difference Water Index (NDWI) was used to map the extent of flooding, while the Normalized Difference Vegetation Index (NDVI) was used to identify vegetation disturbances associated with the landslide. Raster classification, elevation analysis, vector-layer overlay, and thematic mapping were subsequently used to delineate disaster-affected areas and examine their spatial relationships with built-up areas, hydrographic features, and terrain morphology. The results show that the Copernicus Data Space Ecosystem and QGIS provide a transparent and cost-effective analytical environment for the preliminary assessment of natural disaster impacts. In the Wrocław case, the NDWI helped identify flooded areas and infrastructure potentially exposed to flooding. In the Batang Kali case, differences in NDVI helped identify patterns of vegetation disturbance associated with the landslide-affected area. The study demonstrates that open-source geospatial tools can support repeatable natural disaster analysis, geospatial education, and early-stage decision support for disaster risk reduction.
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