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| DOI | 10.1016/j.ecolind.2024.111847 |
| Understanding fine-scale heat health risks and the role of green infrastructure based on remote sensing and socioeconomic data in the megacity of Beijing, China | |
| 发表日期 | 2024 |
| ISSN | 1470-160X |
| EISSN | 1872-7034 |
| 起始页码 | 160 |
| 卷号 | 160 |
| 英文摘要 | The frequency and intensity of extreme heat events have been increasing due to the combined effects of global climate change and urbanization. Urban green infrastructure, including urban green and blue space, has been recognized as an effective measure to mitigate urban heat. However, the effects of green infrastructure on heat health risk were insufficiently addressed. To address this gap, we conducted a comprehensive assessment in the megacity of Beijing with a rapidly aging population. Various data sources were collected, including remote sensing images, meteorological data from weather stations, point of interest(POI) data, and social statistics. Following the risk triangle theory, the hazard, population exposure, and social vulnerability components of heat health risk were evaluated at the census tract level. The weights of vulnerability indicators were determined using Principal Component Analysis. Moran's I and Getis-Ord Gi* statistics were used to identify risk hotspot areas. To evaluate the effects of green infrastructure on heat health risk, a Green Infrastructure Index (GII) was created to quantitatively measure the abundance and accessibility of green infrastructure. The analysis, using a spatially-explicit Heat Health Risk Index (HHRI), indicated that the HHRI in the central urban area inhabited by high-income population groups is 2.66 times that of its suburban counterpart. The primary driving factors of heat health risk were identified as high population density and elevated temperatures. Census tracts with abundant green infrastructure exhibited a low likelihood of becoming high-risk areas, with a probability of less than 2%, while regions with limited green infrastructure had a 54.26% probability of becoming high-risk areas. This highlights the significance of expanding the coverage of green spaces and water areas to reduce heat health risk. The findings provide valuable insights for the development of risk mitigation measures enhancing urban thermal resilience through nature-based climate adaptation. |
| 英文关键词 | Heat Health Risk Index; Urban green space; SDG11.7; Nature -based solutions |
| 语种 | 英语 |
| WOS研究方向 | Biodiversity & Conservation ; Environmental Sciences & Ecology |
| WOS类目 | Biodiversity Conservation ; Environmental Sciences |
| WOS记录号 | WOS:001204770200001 |
| 来源期刊 | ECOLOGICAL INDICATORS
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/290987 |
| 作者单位 | Chang'an University; China Meteorological Administration; Chinese Academy of Sciences; Aerospace Information Research Institute, CAS; Nankai University; Beijing University of Civil Engineering & Architecture; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Chinese Academy of Sciences; Aerospace Information Research Institute, CAS |
| 推荐引用方式 GB/T 7714 | . Understanding fine-scale heat health risks and the role of green infrastructure based on remote sensing and socioeconomic data in the megacity of Beijing, China[J],2024,160. |
| APA | (2024).Understanding fine-scale heat health risks and the role of green infrastructure based on remote sensing and socioeconomic data in the megacity of Beijing, China.ECOLOGICAL INDICATORS,160. |
| MLA | "Understanding fine-scale heat health risks and the role of green infrastructure based on remote sensing and socioeconomic data in the megacity of Beijing, China".ECOLOGICAL INDICATORS 160(2024). |
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