Public responses to heatwaves in Chinese cities: A social media-based geospatial modelling approach

• Geo-located social media is used to quantify public attention to heatwaves. • Physical and socio-economic factors had differentiated effects on heat awareness. • Heat-sensitive city groups were identified based on the coefficients of MGWR. Increasing exposure to heatwaves threatens public health, challenging various socioeconomic sectors in the coming decades. Prior studies mostly concentrated on the heatwaves occurring in specific regions by examining temperature durations, ignoring the fact that heatwaves typically swept across a large area. To comprehensively assess the effects of heatwaves, we jointly analyzed public attention to heatwaves using a dataset of over 10 million geo-located Weibo tweets across 321 cities in China. By considering spatial disparities, two kinds of public attention at city level, namely the number of heat-related tweets (NHTs) and the ratio of heat-related tweets (RHTs), were designed to indicate the severity and location of heatwave impacts, respectively. The heat cumulative intensity was used as a proxy for heatwaves, which exhibited more significant correlations with RHTs than NHTs. The multiscale geographically weighted regression (MGWR) model was employed to investigate the spatiotemporal variations of environment, demographic, and economic-social factors. Six city groups were clustered with MGWR coefficients that were consistent with the seven geographic subregions of China. This research provides a new perspective and methodology for public attention to heatwaves using geo-located social sensing data and highlights the need for actions to mitigate future heatwave stress in sensitive cities.

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Publication Details

Journal
International Journal of Applied Earth Observation and Geoinformation
Published
2024-10-06
DOI
https://doi.org/10.1016/j.jag.2024.104205
Citations
7
Primary Topic
Human Mobility and Location-Based Analysis
Type
article
Field-Weighted Citation Impact
4.78

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article

Public responses to heatwaves in Chinese cities: A social media-based geospatial modelling approach

Yanyan Gu, Mingxuan Dou, Mengling Qiao, Dongyang Wang et al.
7 citations
International Journal of Applied Earth Observation and Geoinformation
Human Mobility and Location-Based Analysis
4.78
article

Public responses to heatwaves in Chinese cities: A social media-based geospatial modelling approach

Yanyan Gu, Mingxuan Dou, Mengling Qiao, Dongyang Wang, Jianya Gong, Yandong Wang
article en
7 citations

Abstract

• Geo-located social media is used to quantify public attention to heatwaves. • Physical and socio-economic factors had differentiated effects on heat awareness. • Heat-sensitive city groups were identified based on the coefficients of MGWR. Increasing exposure to heatwaves threatens public health, challenging various socioeconomic sectors in the coming decades. Prior studies mostly concentrated on the heatwaves occurring in specific regions by examining temperature durations, ignoring the fact that heatwaves typically swept across a large area. To comprehensively assess the effects of heatwaves, we jointly analyzed public attention to heatwaves using a dataset of over 10 million geo-located Weibo tweets across 321 cities in China. By considering spatial disparities, two kinds of public attention at city level, namely the number of heat-related tweets (NHTs) and the ratio of heat-related tweets (RHTs), were designed to indicate the severity and location of heatwave impacts, respectively. The heat cumulative intensity was used as a proxy for heatwaves, which exhibited more significant correlations with RHTs than NHTs. The multiscale geographically weighted regression (MGWR) model was employed to investigate the spatiotemporal variations of environment, demographic, and economic-social factors. Six city groups were clustered with MGWR coefficients that were consistent with the seven geographic subregions of China. This research provides a new perspective and methodology for public attention to heatwaves using geo-located social sensing data and highlights the need for actions to mitigate future heatwave stress in sensitive cities.

International Journal of Applied Earth Observation and GeoinformationVol. 134
Wuhan University (CN), State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (CN), Columbia University (US)
National Natural Science Foundation of China, China Postdoctoral Science Foundation
Openalex Percentile: Top 6%
Human Mobility and Location-Based Analysis
4.78
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