Abstract
The ghost city phenomenon is a serious problem resulting from the rapid urbanization process in China. Estimation of the ghost city rate (GCR) can provide information about vacant dwellings. This paper developed a methodology to quantitatively evaluate GCR values at the national scale using multi-resource remote sensing data. The Suomi National Polar-Orbiting Partnership–Visible Infrared Imaging Radiometer (NPP-VIIRS) night-time light data and moderate resolution imaging spectroradiometer (MODIS) land cover data were used in the evaluation of the GCR values in China. The average ghost city rate (AGCR) was 35.1% in China in 2013. Shanghai had the smallest AGCR of 21.7%, while Jilin has the largest AGCR of 47.27%. There is a significant negative correlation between both the provincial AGCR and the per capita disposable income of urban households (R = −0.659, p < 0.01) and the average selling prices of commercial buildings (R = −0.637, p < 0.01). In total, 31 ghost cities are mainly concentrated in the economically underdeveloped inland provinces. Ghost city areas are mainly located on the edge of urban built-up areas, and the spatial pattern of ghost city areas changed in different regions. This approach combines statistical data with the distribution of vacant urban areas, which is an effective method to capture ghost city information.
Highlights
China has experienced rapid urbanization in the last decades [1]
When correcting the NPP-VIIRS day and night band (DNB) data to extract the built-up area, the maximum brightness of the central urban area can be equal to the maximum threshold of the night-time light (NTL) data [41]
To improve the comparability and visual accuracy of the ghost city rate (GCR), the seriousness of the ghost city phenomenon was described in different administrative regions
Summary
China has experienced rapid urbanization in the last decades [1]. Between 1978 and 2012, China’s urban population increased from 12.9 to 52.6% [2]. The temporal resolution of the data was different (2010 and 2013), and the analysis did not take into account the influence of the Chinese Spring Festival During this period (from January to March), a large portion of the urban population returned to their hometowns, and the ghost city phenomenon appeared in large cities for a short time. Yao et al [14] studied the Chinese housing vacancy rate with DMSP-OLS stable night-time light data. Chen et al [15] used NPP-VIIRS night-time light data and high resolution land use data to estimate the housing vacancy rate in the United States with good results. The NPP-VIIRS night-time light and moderate resolution imaging spectroradiometer (MODIS) land cover data were selected for the extraction of China’s ghost cities. This study had two main objectives: (1) to develop a methodology for estimating China’s ghost city rate; and (2) to obtain the distribution and morphological characteristics of the ghost cities in China
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