Continuing global warming and urbanization have increased the frequency and severity of extreme heat events in cities. Therefore, understanding how the urban heat island (UHI) effect influences cities is essential for developing effective mitigation and prevention strategies. A 1-km resolution dataset was constructed to assess heat-wave exposure attributable to UHIs in urban human settlements worldwide from 2003 to 2020. An adaptive urban-rural threshold method was employed to delineate the spatial extent of UHI impacts, and a spatiotemporally fitted MODIS surface temperature dataset was used to address missing data caused by cloud contamination. This dataset explicitly separates the contributions of background climate, local landscape characteristics, and urbanization to heat wave exposure, providing a scientific basis for identifying key UHI mitigation areas and developing heat wave risk early warning models that account for UHI effects. The proposed methodology and dataset support synergistic decision-making for integrating urban climate adaptation with sustainable development, and the technical framework can be extended to studies of UHIs and heat wave exposure in other regions worldwide.
Yu et al. (Sat,) studied this question.