Spatially explicit assessment of heat health risk in the Yangtze River Delta, China using multi-source remote sensing and socio-economic data

With frequent extreme heat events (EHEs), rapid urbanization, and uneven social development, the impact of EHEs on health has attracted increasing attention. Comprehensive assessment of heat-related health risks is important for tolerating hot weather. To address the limitations of previous assessment methods in regard to the appropriateness of indicators and the fineness of mapping scales, in this paper, we proposed a quantitative method for assessing heat-related health risks at the grid scale. A combination of multisource remote sensing data and demographic-socioeconomic data was utilized to develop an integrated heat health risk index (HRI) that considers the three dimensions of heat hazards, human exposure, and vulnerability in the Yangtze River Delta (YRD). Compensating for the limitations of land surface temperature (LST) and meteorological station data, daily maximum and minimum air temperatures were retrieved to characterize heat hazards and subsequently calculate the hazard index. Gridded population density data were also developed based on nighttime light data to calculate the exposure index. Multidimensional indicators were derived to describe vulnerability, including demographic characteristics, socioeconomic conditions, infrastructure status, governance, and medical resources. By combining the hazard, exposure, and vulnerability indices, an HRI map of the YRD was developed. Furthermore, the spatial heterogeneity and the dominant factors of the heat health risk were examined. The high-risk areas were predominantly concentrated in southern Jiangsu, the Shanghai-Hangzhou Bay urban agglomeration, and the central urban area of prefecture-level cities. This phenomenon suggests synergy between increased human exposure and heat hazards in these metropolitan areas. Due to a low economic development level, the resilience against heat risks in underdeveloped regions such as northern Anhui is low. This study contributes to the identification of areas vulnerable to heat stress, which can help decision-makers optimize local urban heat risk management strategies.