The catastrophic impact of Hurricane Helene proved that standard FEMA flood maps are often inadequate for assessing risk in complex mountainous terrain. Using Buncombe County, North Carolina, as a case study, this research introduces a replicable framework for siting emergency shelters based on a multi-dimensional Flood Risk Index. By synthesizing HAND-derived inundation data, land-use intensity, and a machine learning-based Socio-Economic Vulnerability Index (SEVI), we mapped the intersection of hazard and vulnerability. Our analysis reveals a significant misalignment—a large portion of the current shelter network sits in high-risk zones, while safer upland corridors in the north and west remain underutilized. This study delivers a data-driven roadmap for disaster preparedness, ensuring that future shelter placement is not only safe from terrain-driven floods but also strategically and equitably located.

This study examines historical wildfire frequency and the burned area in the Palisades region from 1928 to 2021 and the spatial distribution of burn severity within the 2025 Palisades Fire perimeter in Los Angeles County, California. Sentinel-2 imagery was used to calculate the Normalized Difference Vegetation Index (NDVI), differenced NDVI (dNDVI), and differenced Normalized Burn Ratio (dNBR). Burn-severity clustering was evaluated with Global and Local Moran’s I and Getis-Ord Gi*, and prefire land cover was summarized from Dynamic World V1. The historical record showed an overall increase in annual fire frequency, while annual burned area remained highly variable. Within the 2025 fire perimeter, the highest dNBR severity class represented 61.92% of the classified area, and Global Moran’s I indicated strong positive spatial autocorrelation (I = 0.874, z = 2656.89, p < 0.001). NDVI and dNDVI showed widespread reductions in vegetation greenness between the prefire and early postfire observation periods. An external field-informed cross-check against the final USGS Burned Area Emergency Response Soil Burn Severity product produced a moderately strong positive rank correlation (Spearman’s ρ = 0.70), although study-specific field validation was unavailable. Area-weighted American Community Survey data provide a descriptive demographic profile of intersecting census tracts and are not interpreted as a population-weighted social vulnerability assessment. The results characterize spatial fire effects and demographic context while avoiding causal attribution to environmental or social drivers that were not directly tested.