A Study on Residential Community-Level Housing Vacancy Rate Based on Multi-Source Data: A Case Study of Longquanyi District in Chengdu City
Source abstract
Abstract
As a pillar industry of China’s economy, the real estate sector has been challenged by the increasing prevalence of housing vacancies, which negatively impacts market stability. Traditional vacancy rate estimation methods, relying on labor-intensive surveys and lacking official statistical support, are limited in accuracy and scalability. To address these challenges, this study proposes a novel framework for assessing residential community-level housing vacancy rates through the integration of multi-source data. Its core is based on night-time lighting data, supplemented by other multi-source big data, for housing vacancy rate (HVR) estimation and practical validation. In the case study of Longquanyi District in Chengdu City, the main conclusions are as follows: (1) with low data resolution, the model estimates a root mean square error (RMSE) of 0.14, which is highly accurate; (2) the average housing vacancy rate (HVR) of houses in Longquanyi District’s residential community is 46%; (3) the HVR rises progressively with the increase in the distance from the city center; (4) the correlation between the HVR of Longquanyi District and the house prices of the area is not obvious; (5) the correlation between the HVR of Longquanyi District and the time of completion of the communities in the region is not obvious, but the newly built communities have extremely high HVR. Compared to the existing literature, this study innovatively leverages multi-source big data to provide a scalable and accurate solution for HVR estimation. The framework enhances understanding of urban real estate dynamics and supports sustainable city development.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Impact of Light on Environment and Health · Building Energy and Comfort Optimization · Housing Market and Economics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
The Faculty Geography Resources Sciences, Sichuan Normal University, Chengdu 610101, China
Key Laboratory of Land Resources Evaluation and Monitoring in Southwest China, Sichuan Normal University, Chengdu 610066, China
Funding
Humanities and Social Sciences Foundation of the Ministry of Education of the People’s Republic of China · The Key Project of Sichuan Provincial Science and Technology Program · The National Natural Science Foundation of China (NSFC)
References (42)
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