Extreme heat events, or heatwaves, exert significant impacts on human society, ecosystems, and the economy. The continuous development of remote sensing technology has facilitated the acquisition of high-quality data for assessing health risks associated with these extreme heat events. This study systematically reviews the evaluation factors and assessment framework for a spatially explicit assessment of heat-related health risks. The contribution of geospatial big data, with a particular focus on satellite observations, to these assessments was investigated. The Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat surface temperature (LST) are identified as the two most widely utilized data sources for mapping heat hazards. The incorporation of multi-sensor observations, along with the implementation of spatiotemporal fusion and downscaling techniques, enhances both the spatial resolution and temporal frequency of heat hazard characterization. It is essential to consider issues of justice and equality in heat-resilient planning and mitigation practices. Integrating heatwave risk assessment results with analyses of urban morphology, land use functions and infrastructure can provide critical information for government agencies to strategically plan urban layout, functions, and public service facilities while optimizing and enhancing urban green infrastructures.
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