Developing a Population-Density-Weighted Community Health Vulnerability Index for Heat and Air Quality to Support Targeted Public Health Interventions: A Multihazard Assessment Using Remotely Sensed and Socio-economic Data in Los Angeles

• Developed a population-density-weighted health vulnerability index (CHVIP) for Los Angeles. • Integrated remote sensing, health, and socio-economic data to map environmental injustice. • 45% of LA’s population resides in very high vulnerability zones, concentrated in the south. • CHVIP reveals structural inequities rooted in historical redlining and underinvestment. • Hotspots align with low-income, minority neighborhoods facing heat and air pollution. Environmental injustice remains a critical challenge in rapidly urbanizing regions, particularly in cities characterized by profound socio-economic inequalities. While natural and anthropogenic hazards such as extreme heat and air pollution are widespread, their impacts are not evenly distributed; vulnerability emerges where environmental exposure intersects with social disadvantage and limited adaptive capacity. This study develops and applies a novel Population-Density-Weighted Community Health Vulnerability Index (CHVI-P) to assess the spatial distribution of combined environmental and socioeconomic vulnerabilities in Los Angeles. This study integrates satellite remote sensing data, including Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) products for urban heat island identification and Sentinel-5P observations for atmospheric pollutant monitoring Nitrogen Dioxide (NO₂), Sulfur Dioxide (SO₂), Carbon Monoxide (CO), Formaldehyde (HCHO), and surface ozone (O₃), with authoritative institutional datasets, namely CalEnviroScreen and the Disease Control and Prevention (CDC’s) Social Vulnerability Index (SVI), to assess community health and socio-economic conditions across Los Angeles. To achieve this, a correlation matrix was first constructed among 19 environmental and socioeconomic parameters. Subsequently, after preparing the required components, the CHVI-P was calculated by integrating exposure (E), sensitivity (S), adaptive capacity (A), and population-density. Finally, spatial clustering patterns of the index were examined using Moran’s I and the Getis-Ord Gi* statistics. The spatial clustering analysis confirms that vulnerability follows non-random, structurally embedded patterns, disproportionately exposing low-income and racial minority communities to environmental hazards. Moreover, findings indicate that approximately 45% of the population resides in areas classified as very high vulnerability, primarily in southern and central neighborhoods. These results underscore the pressing need for targeted, evidence-based policies to address systemic environmental inequities especilaly in an ideal world with no data limitations.