{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T16:46:50Z","timestamp":1783529210552,"version":"3.55.0"},"reference-count":45,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2025,8,11]],"date-time":"2025-08-11T00:00:00Z","timestamp":1754870400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Guangxi Innovation and Entrepreneurship Training Program for College Students","award":["202510603320"],"award-info":[{"award-number":["202510603320"]}]},{"name":"Guangxi Innovation and Entrepreneurship Training Program for College Students","award":["60203038919630213"],"award-info":[{"award-number":["60203038919630213"]}]},{"name":"Guangxi Innovation and Entrepreneurship Training Program for College Students","award":["602021239447"],"award-info":[{"award-number":["602021239447"]}]},{"name":"Research funding for the 2024 Green seedling Program of the Human Resources and Social Security Department of Guangxi Zhuang Autonomous Region, China","award":["202510603320"],"award-info":[{"award-number":["202510603320"]}]},{"name":"Research funding for the 2024 Green seedling Program of the Human Resources and Social Security Department of Guangxi Zhuang Autonomous Region, China","award":["60203038919630213"],"award-info":[{"award-number":["60203038919630213"]}]},{"name":"Research funding for the 2024 Green seedling Program of the Human Resources and Social Security Department of Guangxi Zhuang Autonomous Region, China","award":["602021239447"],"award-info":[{"award-number":["602021239447"]}]},{"name":"Nanning Normal University Doctoral Research Startup Project","award":["202510603320"],"award-info":[{"award-number":["202510603320"]}]},{"name":"Nanning Normal University Doctoral Research Startup Project","award":["60203038919630213"],"award-info":[{"award-number":["60203038919630213"]}]},{"name":"Nanning Normal University Doctoral Research Startup Project","award":["602021239447"],"award-info":[{"award-number":["602021239447"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Housing vacancy rate is a key indicator for evaluating urban sustainable development. Due to rapid urbanization, population outflow and insufficient industrial support, the housing vacancy problem is particularly prominent in China\u2019s underdeveloped regions. However, the lack of official data and the limitations of traditional survey methods restrict in-depth research. This study proposes a vacancy rate estimation method based on Baidu Street View residential exterior images and deep learning technology. Taking Nanning, Guangxi as a case study, an automatic discrimination model for residential vacancy status is constructed by identifying visual clues such as window occlusion, balcony debris accumulation, and facade maintenance status. The study first uses Baidu Street View API to collect images of residential communities in Nanning. After manual annotation and field verification, a labeled dataset is constructed. A pre-trained deep learning model (ResNet50) is applied to estimate the vacancy rate of the community after fine-tuning with labeled street view images of Nanning\u2019s residential communities. GIS spatial analysis is combined to reveal the spatial distribution pattern and influencing factors of the vacancy rate. The results show that street view images can effectively capture vacancy characteristics that are difficult to identify with traditional remote sensing and indirect indicators, providing a refined data source and method innovation for housing vacancy research in underdeveloped regions. The study further found that the residential vacancy rate in Nanning showed significant spatial differentiation, and the vacancy driving mechanism in the old urban area and the emerging area was significantly different. This study expands the application boundaries of computer vision in urban research and fills the research gap on vacancy issues in underdeveloped areas. Its results can provide a scientific basis for the government to optimize housing planning, developers to make rational investments, and residents to make housing purchase decisions, thus helping to improve urban sustainable development and governance capabilities.<\/jats:p>","DOI":"10.3390\/a18080500","type":"journal-article","created":{"date-parts":[[2025,8,11]],"date-time":"2025-08-11T11:02:09Z","timestamp":1754910129000},"page":"500","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Estimation of Residential Vacancy Rate in Underdeveloped Areas of China Based on Baidu Street View Residential Exterior Images: A Case Study of Nanning, Guangxi"],"prefix":"10.3390","volume":"18","author":[{"given":"Weijia","family":"Zeng","sequence":"first","affiliation":[{"name":"School of Geography and Planning, Nanning Normal University, Nanning 530001, China"},{"name":"Key Laboratory of Environment Change and Resources Use in Beibu Gulf, Ministry of Education, Nanning Normal University, Nanning 530001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8376-1694","authenticated-orcid":false,"given":"Binglin","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Geography and Planning, Nanning Normal University, Nanning 530001, China"},{"name":"Key Laboratory of Environment Change and Resources Use in Beibu Gulf, Ministry of Education, Nanning Normal University, Nanning 530001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Geography and Planning, Nanning Normal University, Nanning 530001, China"},{"name":"Urban Planning and Design Institute of Nanjing University Co., Ltd., Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8705-566X","authenticated-orcid":false,"given":"Weijiang","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Engineering, City University of Hong Kong, Hong Kong 99077, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuhe","family":"Fu","sequence":"additional","affiliation":[{"name":"School of Architecture and Art Design, Lanzhou University of Technology, Lanzhou 620103, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiyue","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Life Science, Hubei University, Wuhan 430062, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiran","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Business Administrations, Zhongnan University of Economics and Law, Wuhan 430073, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Wuyts, W., Sedlitzky, R., Morita, M., and Tanikawa, H. 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