Frequent and severe heat waves have posed significant threats to residents' emotional well-being. Traditional questionnaire survey data struggled to obtain timely, large-scale emotional responses to heat waves. This study employed multi-source geographic big data to explore spatial heterogeneities in the impacts of heat waves on emotions and to investigate their potential causal factors. Firstly, social media Weibo data were employed to extract fine-grained emotional information. Then, remote sensing imagery (e.g., Sentinel-2, DMSP-OLS) and point-of-interest (POI) data were integrated to characterize the urban built environment. This research elucidated the spatial heterogeneities of heat waves impact on emotions and further examined their causal relationships with built environment factors using spatial analysis methods and the Geographical Convergent Cross Mapping (GCCM) method. The results revealed significant spatial heterogeneities in emotional expressions during heat waves. Residents in the suburban areas tended to express “surprise” and “happy” whereas residents in central urban areas often expressed “good” and “sadness”. GCCM analysis showed that emotions such as “happy” “surprise” “fear” and “anger” had stronger causal associations with urban functional indicators, including the normalized difference vegetation index (NDVI), nighttime light intensity (NTL). In contrast, POI entropy density and the normalized difference built-up index (NDBI) were exhibited relatively weak. This research provided new insights into the spatial heterogeneities and driving mechanisms of the impact of heat waves on emotions, sup-porting in-depth targeted and differentiated public health strategies under climate extremes.
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Funding
National Natural Science Foundation of China(42471272)
Beijing Union University(No. ZK10202209)
RIGHTS & PERMISSIONS
The Author(s)
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