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Global sea level rise (SLR) has emerged as a pressing concern because of its impacts, especially increased vulnerability of coastal urban areas flooding. This study addresses the pressing concern of SLR and flood vulnerability in the East Coast of North Sumatra (ECNS) and Medan City. We employ a data-driven approach integrating multicriteria analysis, analytical hierarchy process (AHP)-based weighting, and spatial modeling within a geographic information system framework. The analysis considers crucial factors such as slope, land use, soil type, SLR, and land deformation. The study expands the existing framework by incorporating SLR and land subsidence, acknowledging their significant roles in exacerbating flood vulnerability. Future flood-intensity scenarios are simulated based on SLR projections. Data for spatial analysis primarily originated from multisensor satellite imagery, secondary sources from published literature, and field surveys. We validated the consistency of the variable weightings assigned for vulnerability analysis using a consistency ratio threshold (<0.1). Finally, the established flood vulnerability model was validated by comparing its predictions with recorded flood events in the ECNS and Medan City. The ECNS and Medan City areas were classified as very high and highly vulnerable to flooding, respectively.

来源平台：REMOTE SENSING