A Remote Sensing-Based Vacancy Area Index For Estimating Housing Vacancy And Ghost Cities In China

Housing vacancy data, providing useful information on building occupancy rates, are used extensively by public and private organizations to evaluate the need for new housing development programs and also the vacancy rate is regarded as a leading indicator to measure the economic climate. Such a topic has received considerable attentions in China due to its overheated real estate development. Previous house vacancy studies use governmental statistics or private user positioning data, the collection of which is time consuming and difficult. In this work, an efficient indicator Vacancy Area Index (VAI), ranging from 0 to 10, is proposed to measure the county level housing occupancy and ghost cities over China based on MODIS products and DMSP-OLS nighttime light data. Results show that VAI is a good measure of house vacancy with a detection rate 94.44% of ghost cities and a precision 92.48% of non-ghost cities. About 320 among 2430 county areas in China have a VAI no less than 7, indicating national wide spread high house vacancy. The VAI can also reveal the spatial characteristics and temporal development of cities with different features such as tourism cites, industrial cities, and real "Ghost Cities" accurately.