Author
Listed:
- Tingting Kang
(School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen 518055, China
Key Laboratory of Earth Surface System and Human-Earth Relations, Ministry of Natural Resources of China, Shenzhen 518055, China)
- Yangyang Jiang
(School of Geography, South China Normal University, Guangzhou 510631, China
Guangdong Provincial Key Laboratory of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China)
- Chuangeng Yang
(School of Geography, South China Normal University, Guangzhou 510631, China
Guangdong Provincial Key Laboratory of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China)
- Yujie She
(School of Geography, South China Normal University, Guangzhou 510631, China
Guangdong Provincial Key Laboratory of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China)
- Zixi Jiang
(School of Geography, South China Normal University, Guangzhou 510631, China
Guangdong Provincial Key Laboratory of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China)
- Zeng Li
(Guangdong Provincial Key Laboratory of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China
Guangdong-Hong Kong-Macau Joint Laboratory for Smart Cities, Shenzhen 518061, China)
Abstract
Although the immediate impact of the COVID-19 pandemic has been alleviated, its long-term effects continue to shape global health and public safety. Policymakers should prepare for potential future health crises and direct urban planning toward more sustainable outcomes. While numerous studies have examined factors influencing the risk of COVID-19, few have investigated the spatial spillover effects of urban form and green space. In this study, we quantified urban form using landscape pattern indices, represented population mobility with the Baidu Migration Scale Index, and assessed the role of key influencing factors on the epidemic through STIRPAT and spatial Durbin models. Our findings reveal that population migration from Wuhan had a significant local impact on the spread of COVID-19. These factors not only intensified local transmission, but also triggered positive spatial spillover effects, spreading the virus to neighboring regions. We also found that green space connectivity ( pc 5 ) plays a crucial role in reducing the spread of the virus, both locally and in surrounding areas. High green space connectivity helps mitigate disease transmission during an epidemic. In contrast, the spatial configuration and unipolarity of urban areas ( pc 1 ) contributed to the increased spread of the virus to neighboring cities. Ultimately, balancing building density with green space distribution is essential for enhancing urban resilience. This research provides new insights into sustainable urban planning and helps us understand the impact of the spillover effects of gray–green space forms on public health and safety.
Suggested Citation
Tingting Kang & Yangyang Jiang & Chuangeng Yang & Yujie She & Zixi Jiang & Zeng Li, 2025.
"Spatial Spillover Effects of Urban Gray–Green Space Form on COVID-19 Pandemic in China,"
Land, MDPI, vol. 14(4), pages 1-31, April.
Handle:
RePEc:gam:jlands:v:14:y:2025:i:4:p:896-:d:1637523
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