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Sophistication of Monitoring Method for Spatial Distribution of Vacant Houses Using Machine Learning

A study on the estimation method of spatial distribution of vacant houses using municipal public data (Part 3)

Bibliographic Data

ID19064112
AuthorsYuki Akiyama (0000-0002-8790-0364, Tokyo City University, corresponding author), Hiroki Baba (0000-0003-2005-4578, Center for Southeast Asian Studies / Hakubi Center for Advanced Research, Kyoto University), Yoshiya Ono (Policy Research Institute for Land Infrastructure, Transport and Tourism, MLIT), Hideo Takaoka (Japan Real Estate Institute)
Year2021
Volume86
Issue786
Pages2136-2146
Publication date2021-08-29
Open AccessYes
TypeARTICLE
VenueJournal of Architecture and Planning (Transactions of AIJ) (JOURNAL)
Journal identifiersISSN: 1340-4210 • E-ISSN: 1881-8161
PublisherArchitectural Institute of Japan (PUBLISHER • JP)
DOI10.3130/aija.86.2136
OpenAlexW3203354386
LanguageEN
Citations received1
References cited9

This study resolved the problem of Part 2 and refined the method for estimating the spatial distribution of vacant houses using public municipal data by addressing the following issues

Machine learning · Sociology · Sophistication · Computer Science · Land Use and Ecosystem Services · Urban and spatial planning · Urbanization and City Planning · Artificial Intelligence

  • Estimation of priority areas for vacant housing control using government statistics

    Open Access•Keisuke Mizutani, Yuki Akiyama et al.•Journal of Housing and the Built…•2025

Citations per year1
Citation span2025 - 2025 (1)
Highly citedNo

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