Urban flood susceptibility and riparian vegetation using GLM-based spatial modelling from vegetation cover in Samarinda, Indonesia
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Abstract. Naufalianto IF, Madjid MIN, Fauzan MRN, Sidiq AR. 2026. Urban flood susceptibility and riparian vegetation using GLM-based spatial modelling from vegetation cover in Samarinda, Indonesia. Asian J For 10 (1): r100115. https://doi.org/10.13057/asianjfor/r100115. Urban flooding in tropical cities is increasingly shaped by land-cover change, yet the contribution of urban vegetation to flood susceptibility remains poorly quantified. This study mapped flood susceptibility in Samarinda, Indonesia, using a Generalized Linear Model (GLM) fitted to 123 spatially thinned flood-presence points derived from georeferenced online reports and 1,000 pseudo-absence points (1:8). Open-source covariates were derived from Sentinel-2 and SRTM, including Enhanced Vegetation Index (EVI), elevation, and built-up occurrence frequency. After screening for multicollinearity and selecting the best minimal model, flood occurrence was negatively associated with EVI and elevation and positively associated with built-up frequency. Model discrimination was high (AUC = 0.959 in a 70/30 split) and remained consistent under spatial block cross-validation, with predictions interpreted as relative susceptibility rather than event-based hydrological simulation. Predicted high susceptibility was concentrated along low-lying river corridors and densely built zones, whereas vegetated and elevated areas exhibited lower susceptibility. Jenks classification indicated 4.74% of the study area in the high class. These findings highlight the importance of maintaining urban vegetation cover, particularly urban riparian forests and green belts, as a nature-based component of flood-risk reduction. The susceptibility map can be used as a consideration for urban forestry planning by prioritizing riparian forest conservation and restoration in river-corridor segments with high predicted susceptibility.
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