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

Heliyon(2023)

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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.
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Key words
Housing vacancy rate,Housing vacancy stock,Remote sensing data,LMDI decomposition Method
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