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dc.contributor.authorCong, Cong
dc.contributor.authorPage, Jessica
dc.contributor.authorKwak, Yoonshin
dc.contributor.authorDeal, Brian
dc.contributor.authorKalantari, Zahra
dc.date.accessioned2024-10-11T21:24:23Z
dc.date.available2024-10-11T21:24:23Z
dc.date.issued2024-08-01
dc.identifier.urihttps://hdl.handle.net/1721.1/157266
dc.description.abstractArtificial intelligence (AI) has become a transformative force across various disciplines, including urban planning. It has unprecedented potential to address complex challenges. An essential task is to facilitate informed decision making regarding the integration of constantly evolving AI analytics into planning research and practice. This paper presents a review of how AI methods are applied in urban studies, focusing particularly on carbon neutrality planning. We highlight how AI is already being used to generate new scientific knowledge on the interactions between human activities and nature. We consider the conditions in which the advantages of AI-enabled urban studies can positively influence decision-making outcomes. We also consider the importance of interdisciplinary collaboration, responsible AI governance, and community engagement in guiding data-driven methods and suggest how AI can contribute to supporting carbon-neutrality goals.en_US
dc.publisherMultidisciplinary Digital Publishing Instituteen_US
dc.relation.isversionofhttp://dx.doi.org/10.3390/urbansci8030104en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceMultidisciplinary Digital Publishing Instituteen_US
dc.titleAI Analytics for Carbon-Neutral City Planning: A Systematic Review of Applicationsen_US
dc.typeArticleen_US
dc.identifier.citationCong, C.; Page, J.; Kwak, Y.; Deal, B.; Kalantari, Z. AI Analytics for Carbon-Neutral City Planning: A Systematic Review of Applications. Urban Sci. 2024, 8, 104.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Urban Studies and Planningen_US
dc.identifier.mitlicensePUBLISHER_CC
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.updated2024-09-27T13:18:12Z
dspace.date.submission2024-09-27T13:18:12Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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