Spatial Identification of Housing Vacancy in China
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Springer Science Press www.springerlink.com/content/1002-0063
Spatial Identification of Housing Vacancy in China PAN Jinghu1, DONG Leilei1, 2 (1. College of Geography and Environmental Sciences, Northwest Normal University, Lanzhou 730070, China; 2. Northwest Institute of Eco-Environment and Resources, Lanzhou 730000, China) Abstract: The housing vacancy rate (HVR) is an important index in assessing the healthiness of residential real estate market. In China, it is hardly to take advantage of the basic data of real estate information due to the opaque of those data. In this paper, the HVR is estimated to two scales. At the grid level, urban area ratio was calculated by nighttime images after eliminating outliers of nighttime images and night light intensity of non-residential pixels in mixed pixels by a proposed modified optimal threshold method, and built-up areas in each pixel were extracted from the land-cover data. Then, the HVR is calculated by comparing the light intensity of specific grid with the light intensity of full occupancy rate regions. At the administrative scale, the GCI (‘ghost city’ index) is constructed by calculating the ratio of the total light radiation intensity of a city to the total construction land area of the city. The overall spatial differentiation pattern of the vacant houses in the national prefecture level administrative regions is analyzed. The following conclusions were drawn: vacant housing is rare in certain eastern coastal cities and regions in China with relatively fast economic development. Cities based on exhausted resources, some mountainous cities, and cities with relatively backward economic development more typically showed high levels of housing vacancy. The GCI of prefecture-level administrative units gradually declined from north to south, whereas the east-west distribution showed a parabolic shape. As city level decreased, the GCI registered a gradual upward trend. China’s urban housing vacancy can be divided into five categories: industry or resources driven, government planned, epitaxy expansionary, environmental constraint and speculative activate by combining the spatial distribution of housing vacancy with the factors of natural environment, social economic development level, and population density into consideration. Keywords: housing vacancy rate (HVR); spatial identification; nighttime light; spatial pattern; ghost city; China Citation: PAN Jinghu, DONG Leilei. Spatial Identification of Housing Vacancy in China. Chinese Geographical Science. https://doi. org/10.1007/s11769-020-1171-7
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Introduction
Housing is for living, not for speculation, and even less for being left vacant. As a pillar industry of the national economy, the real estate industry occupies a crucial position in developing the national economy (Gabriel and Nothaft, 2001; Mittal and Kashyap, 2015). The steady development of the real estate market directly affects residents’ quality of life, and the housing vacancy rate (HVR) is a significant indicator of the health of the real
estate market
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