Global dataset on heat wave exposure due to the urban heat island effect

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.

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Publication Details

Journal
Scientific Data
Published
2026-02-14
DOI
https://doi.org/10.1038/s41597-026-06877-1
Primary Topic
Urban Heat Island Mitigation
Type
article
Field-Weighted Citation Impact
0.00

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article

Global dataset on heat wave exposure due to the urban heat island effect

Jie Yang, Wenbo Yu, Xiangming Xiao, Yuyu Zhou
Scientific Data
Urban Heat Island Mitigation
article

Global dataset on heat wave exposure due to the urban heat island effect

Jie Yang, Wenbo Yu, Xiangming Xiao, Yuyu Zhou
article en

Abstract

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.

Scientific DataVol. 13(1)
Liaoning Normal University (CN), University of Oklahoma (US), University of Hong Kong (HK), Northeastern University (CN), Hebei Normal University (CN)
Liaoning Revitalization Talents Program
Climate action
Openalex Percentile: Top 61%
Urban Heat Island Mitigation
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Global dataset on heat wave exposure due to the urban heat island effect — Jie Yang, Wenbo Yu, et al. · Scientific Data (2026) | TGRS Research Map | TGRS