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dc.contributor.authorHan, Zhenyu
dc.contributor.authorZhang, Xin
dc.contributor.authorXi, Yanxin
dc.contributor.authorLuo, Yan
dc.contributor.authorXia, Tong
dc.contributor.authorLi, Yong
dc.date.accessioned2024-12-05T21:27:40Z
dc.date.available2024-12-05T21:27:40Z
dc.date.issued2024-10-29
dc.identifier.isbn979-8-4007-1107-7
dc.identifier.urihttps://hdl.handle.net/1721.1/157761
dc.descriptionSIGSPATIAL ’24, October 29-November 1, 2024, Atlanta, GA, USAen_US
dc.description.abstractThe substantial social and financial costs of infrastructure identification impede in-depth analyses of sustainable urban design, especially in developing countries. In this paper, we present a novel framework with interactive web visualization based on geospatial visual foundation models. Leveraging this framework, we examine the urban infrastructure information in 1,178 cities worldwide, covering 93, 088 km2 areas. Cross-validation reveals that the overall accuracy of identified infrastructure achieves 67.0%. It sheds light on the sustainable development of cities and exposes the stark inequity in urban infrastructure provision for vulnerable populations. The identified urban infrastructure dataset of this study are available at https://github.com/tsinghua-fib-lab/GUI, and the interactive web application is at https://tinyurl.com/yz7xbfy3.en_US
dc.publisherACM|The 32nd ACM International Conference on Advances in Geographic Information Systemsen_US
dc.relation.isversionofhttps://doi.org/10.1145/3678717.3691242en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceAssociation for Computing Machineryen_US
dc.titleGUI: A Comprehensive Dataset of Global Urban Infrastructure Based on Geospatial Visual Foundation Modelsen_US
dc.typeArticleen_US
dc.identifier.citationHan, Zhenyu, Zhang, Xin, Xi, Yanxin, Luo, Yan, Xia, Tong et al. 2024. "GUI: A Comprehensive Dataset of Global Urban Infrastructure Based on Geospatial Visual Foundation Models."
dc.contributor.departmentMassachusetts Institute of Technology. Media Laboratory
dc.identifier.mitlicensePUBLISHER_POLICY
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2024-12-01T08:47:44Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2024-12-01T08:47:44Z
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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