Sea level rise refers to the long-term increase in ocean water levels driven by thermal expansion and glacial melt, presenting significant risks to coastal infrastructure, ecosystems, and human populations. As a GIS use case, sea level rise analysis leverages geospatial data, remote sensing imagery, and digital elevation models (DEMs) to model inundation scenarios across vulnerable coastal zones. GIS professionals integrate datasets from sources such as NOAA, LiDAR surveys, and satellite altimetry to perform spatial analysis that identifies at-risk areas, quantifies land loss projections, and supports evidence-based planning.

Using tools like ArcGIS, QGIS, or cloud-based geospatial platforms, analysts apply raster analysis, hydrological modeling, and flood simulation workflows to visualize how varying sea level increments — typically ranging from 0.5 to 2.0 meters — affect shorelines, wetlands, and urban areas. These mapping outputs support disaster risk reduction, coastal resilience planning, infrastructure prioritization, and climate adaptation strategies. By combining temporal spatial data with predictive modeling, GIS enables decision-makers to anticipate environmental change, allocate resources efficiently, and develop actionable mitigation frameworks grounded in quantifiable geographic intelligence.