Urban Spatial Heat Resilience Indicator Based on Running Activity Z-Score

The assessment of urban heat resilience has become crucial due to increasing extreme weather events. This study introduces the Running Activity Z-score (RAZ) index based on running activity trajectory data to evaluate heat resilience. Through a case study of an August 2022 heatwave in Beijing, we examined the index’s sensitivity to extreme heat and explored its spatial relationships with key built environment factors, including plot ratio, green coverage, population density, and blue space proximity. Our results reveal two key findings: (1) the RAZ index serves as an effective real-time, high-precision indicator of urban heatwave impacts, as evidenced by extremely low RAZ values consistently coinciding with heatwave periods, and (2) the RAZ index offers valuable insights for identifying potential low heat resilience areas and supporting planning decisions, as demonstrated by its significant correlations with built environment factors that align with previous studies while uncovering more detailed spatial relationships. Although RAZ effectively complements traditional measurement methods, its application requires careful consideration of external factors such as social dynamics and climate variability.

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Publication Details

Journal
Urban Science
Published
2025-02-05
DOI
https://doi.org/10.3390/urbansci9020034
Citations
5
Primary Topic
Urban Heat Island Mitigation
Type
article
Field-Weighted Citation Impact
4.00

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article

Urban Spatial Heat Resilience Indicator Based on Running Activity Z-Score

Yuan Lai, Li Zhou
5 citations
Urban Science
Urban Heat Island Mitigation
4.00
article

Urban Spatial Heat Resilience Indicator Based on Running Activity Z-Score

Yuan Lai, Li Zhou
article en
5 citations

Abstract

The assessment of urban heat resilience has become crucial due to increasing extreme weather events. This study introduces the Running Activity Z-score (RAZ) index based on running activity trajectory data to evaluate heat resilience. Through a case study of an August 2022 heatwave in Beijing, we examined the index’s sensitivity to extreme heat and explored its spatial relationships with key built environment factors, including plot ratio, green coverage, population density, and blue space proximity. Our results reveal two key findings: (1) the RAZ index serves as an effective real-time, high-precision indicator of urban heatwave impacts, as evidenced by extremely low RAZ values consistently coinciding with heatwave periods, and (2) the RAZ index offers valuable insights for identifying potential low heat resilience areas and supporting planning decisions, as demonstrated by its significant correlations with built environment factors that align with previous studies while uncovering more detailed spatial relationships. Although RAZ effectively complements traditional measurement methods, its application requires careful consideration of external factors such as social dynamics and climate variability.

Urban ScienceVol. 9(2)
Tsinghua University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 8%
Urban Heat Island Mitigation
4.00
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Urban Spatial Heat Resilience Indicator Based on Running Activity Z-Score — Yuan Lai, Li Zhou · Urban Science (2025) | TGRS Research Map | TGRS