Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/101660
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dc.contributorDepartment of Land Surveying and Geo-Informaticsen_US
dc.creatorChen, Ben_US
dc.creatorTu, Yen_US
dc.creatorWu, Sen_US
dc.creatorSong, Yen_US
dc.creatorJin, Yen_US
dc.creatorWebster, Cen_US
dc.creatorXu, Ben_US
dc.creatorGong, Pen_US
dc.date.accessioned2023-09-18T07:41:08Z-
dc.date.available2023-09-18T07:41:08Z-
dc.identifier.issn0160-4120en_US
dc.identifier.urihttp://hdl.handle.net/10397/101660-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.rightsThe following publication Chen, B., Tu, Y., Wu, S., Song, Y., Jin, Y., Webster, C., ... & Gong, P. (2022). Beyond green environments: multi-scale difference in human exposure to greenspace in China. Environment International, 166, 107348 is available at https://doi.org/10.1016/j.envint.2022.107348.en_US
dc.subjectEnvironmental exposureen_US
dc.subjectEnvironmental justiceen_US
dc.subjectGreen spacesen_US
dc.subjectPopulation-weighted exposureen_US
dc.subjectUrbanizationen_US
dc.titleBeyond green environments : multi-scale difference in human exposure to greenspace in Chinaen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume166en_US
dc.identifier.doi10.1016/j.envint.2022.107348en_US
dcterms.abstractGreenspace 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.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationEnvironment International, Aug. 2022, v. 166, 107348en_US
dcterms.isPartOfEnvironment internationalen_US
dcterms.issued2022-08-
dc.identifier.scopus2-s2.0-85132752631-
dc.identifier.pmid35749992-
dc.identifier.artn107348en_US
dc.description.validate202309 bcvcen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextUniversity of Hong Kong; National Natural Science Foundation of China; National Natural Science Foundation of China; Tsinghua-Toyota Joint Research Funden_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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