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基于多源遥感数据的山东半岛城市群住房空置率评估及驱动因素分析

Assessment and driving factor of housing vacancies in Shandong Peninsula urban agglomeration based on multi-source remote sensing data.

作者信息

Yang Dong, Xiao Bing, Lu Xinjie, Jia Xuexiu, Li Xin, Han Feng, Sun Lingwen, Shi Feng, Khumvongsa Kronnaphat, Li Jinping, Duan Xianyin

机构信息

Institute of Science and Technology for Development of Shandong, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250014, China.

Research Center of SCO Countries, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250014, China.

出版信息

Heliyon. 2023 Jun 2;9(6):e16837. doi: 10.1016/j.heliyon.2023.e16837. eCollection 2023 Jun.

DOI:10.1016/j.heliyon.2023.e16837
PMID:37332965
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10272329/
Abstract

As the urbanization rate in the world has increased rapidly, the housing vacancy problem has become serious and attracting more attention. Calculating and analyzing vacant housing can help reduce the wasteful use of resources. This paper measures the housing vacancy rate and housing vacancy stock in the Shandong Peninsula urban agglomeration using night-time lighting and land use data. The results show that the average housing vacancy rate in the Shandong Peninsula urban agglomeration rose rapidly from 14.68% in 2000 to 29.71% in 2015 before declining slowly to 29.49% in 2020. Since urban population growth is lower than the housing construction rate, the average annual growth of housing vacancy stock between 2000 and 2020 exceeds 3 million square meters in megacities and is around 1-2 million square meters in large and medium-sized cities. The vacant housing has caused considerable waste of housing resources. The driving factors of the housing vacancy were further analyzed using the LMDI decomposition method. Results indicate that the economic development level is the most significant driving factor of the vacant housing stock. In addition, the value effect of unit floor areas is the major driving factor inhibiting the growth of vacant housing stock, while the decline of unit floor area value is conducive to the reduction of this stock.

摘要

随着世界城市化率的迅速提高,住房空置问题日益严重,受到越来越多的关注。计算和分析空置住房有助于减少资源的浪费性使用。本文利用夜间灯光和土地利用数据,对山东半岛城市群的住房空置率和住房空置存量进行了测算。结果表明,山东半岛城市群的平均住房空置率从2000年的14.68%迅速上升至2015年的29.71%,随后缓慢下降至2020年的29.49%。由于城市人口增长低于住房建设率,2000年至2020年期间,特大城市的住房空置存量年均增长超过300万平方米,大中型城市约为100万至200万平方米。空置住房造成了相当大的住房资源浪费。利用LMDI分解法进一步分析了住房空置的驱动因素。结果表明经济发展水平是空置住房存量最显著的驱动因素。此外,单位建筑面积价值效应是抑制空置住房存量增长的主要驱动因素,而单位建筑面积价值的下降有利于减少这一存量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d4f/10272329/874a3c33d38b/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d4f/10272329/e54836f33a70/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d4f/10272329/a694153b6ae5/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d4f/10272329/0cbbc5e6d5d4/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d4f/10272329/3129893ceaf0/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d4f/10272329/874a3c33d38b/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d4f/10272329/e54836f33a70/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d4f/10272329/a694153b6ae5/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d4f/10272329/0cbbc5e6d5d4/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d4f/10272329/3129893ceaf0/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d4f/10272329/874a3c33d38b/gr5.jpg

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本文引用的文献

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