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- Publisher Website: 10.1016/j.envint.2022.107348
- WOS: WOS:000818498400006
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Article: Beyond green environments: Multi-scale difference in human exposure to greenspace in China
Title | Beyond green environments: Multi-scale difference in human exposure to greenspace in China |
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Authors | |
Issue Date | 2022 |
Citation | Environment International, 2022, v. 166, p. 107348 How to Cite? |
Abstract | Greenspace exposure metrics can allow for comparisons of green space supply across time, space, and population groups, and for inferring patterns of variation in opportunities for people to enjoy the health and recreational benefits of nearby green environments. A better understanding of greenspace exposure differences across various spatial scales is a critical requirement for lessening environmental health disparities. However, existing studies are typically limited to a single city or across selected cities, which severely limits the use of results in measuring systemic national and regional scale differences that might need policy at above individual city planning level. To close this knowledge gap, our study aims to provide a holistic assessment of multi-scale greenspace exposure across provinces, cities, counties, towns, and land parcels for the whole of China. We mapped the nationwide fractional greenspace coverage at 10 m with Sentinel-2 satellite imagery, and then modeled population-weighted greenspace exposure to examine variation of greenspace exposure across scales. Our results show a prominent scaling effect of greenspace exposure across multi-scale administrative divisions in China, suggesting, as expected, an increase in heterogeneity with finer spatial scales. We also identify an asymmetric pattern of the difference between greenspace exposure and greenspace coverage, across a geo-demographic demarcation boundary (i.e., along the Heihe–Tengchong Line). In general, the greenspace coverage rate will overestimate more realistic human exposure to greenspace in East China while underestimating in West China. We further found that, in China, more recently urbanized areas have much better greenspace exposure than older urban areas. Our study provides a spatially explicit greenspace exposure metric for discovering multi-scale greenspace exposure difference, which will enhance governments’ capacity to quantify environmental justice, detect vulnerable greenspace exposure risk hotspots, prioritize greenspace management at the supra-city scale, and monitor the balance between greenspace supply and demand. |
Persistent Identifier | http://hdl.handle.net/10722/317756 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Chen, B | - |
dc.contributor.author | Tu, Y | - |
dc.contributor.author | Wu, S | - |
dc.contributor.author | Song, Y | - |
dc.contributor.author | Jin, Y | - |
dc.contributor.author | Webster, CJ | - |
dc.contributor.author | Xu, B | - |
dc.contributor.author | Gong, P | - |
dc.date.accessioned | 2022-10-07T10:26:20Z | - |
dc.date.available | 2022-10-07T10:26:20Z | - |
dc.date.issued | 2022 | - |
dc.identifier.citation | Environment International, 2022, v. 166, p. 107348 | - |
dc.identifier.uri | http://hdl.handle.net/10722/317756 | - |
dc.description.abstract | Greenspace exposure metrics can allow for comparisons of green space supply across time, space, and population groups, and for inferring patterns of variation in opportunities for people to enjoy the health and recreational benefits of nearby green environments. A better understanding of greenspace exposure differences across various spatial scales is a critical requirement for lessening environmental health disparities. However, existing studies are typically limited to a single city or across selected cities, which severely limits the use of results in measuring systemic national and regional scale differences that might need policy at above individual city planning level. To close this knowledge gap, our study aims to provide a holistic assessment of multi-scale greenspace exposure across provinces, cities, counties, towns, and land parcels for the whole of China. We mapped the nationwide fractional greenspace coverage at 10 m with Sentinel-2 satellite imagery, and then modeled population-weighted greenspace exposure to examine variation of greenspace exposure across scales. Our results show a prominent scaling effect of greenspace exposure across multi-scale administrative divisions in China, suggesting, as expected, an increase in heterogeneity with finer spatial scales. We also identify an asymmetric pattern of the difference between greenspace exposure and greenspace coverage, across a geo-demographic demarcation boundary (i.e., along the Heihe–Tengchong Line). In general, the greenspace coverage rate will overestimate more realistic human exposure to greenspace in East China while underestimating in West China. We further found that, in China, more recently urbanized areas have much better greenspace exposure than older urban areas. Our study provides a spatially explicit greenspace exposure metric for discovering multi-scale greenspace exposure difference, which will enhance governments’ capacity to quantify environmental justice, detect vulnerable greenspace exposure risk hotspots, prioritize greenspace management at the supra-city scale, and monitor the balance between greenspace supply and demand. | - |
dc.language | eng | - |
dc.relation.ispartof | Environment International | - |
dc.title | Beyond green environments: Multi-scale difference in human exposure to greenspace in China | - |
dc.type | Article | - |
dc.identifier.email | Chen, B: binleych@hku.hk | - |
dc.identifier.email | Wu, S: shengwu@hku.hk | - |
dc.identifier.email | Webster, CJ: cwebster@hku.hk | - |
dc.identifier.email | Gong, P: penggong@hku.hk | - |
dc.identifier.authority | Chen, B=rp02812 | - |
dc.identifier.authority | Webster, CJ=rp01747 | - |
dc.identifier.authority | Gong, P=rp02780 | - |
dc.identifier.doi | 10.1016/j.envint.2022.107348 | - |
dc.identifier.hkuros | 337554 | - |
dc.identifier.volume | 166 | - |
dc.identifier.spage | 107348 | - |
dc.identifier.epage | 107348 | - |
dc.identifier.isi | WOS:000818498400006 | - |