remote sensing Article
Mapping China’s Ghost Cities through the Combination of Nighttime Satellite Data and Daytime Satellite Data Heli Lu 1, * ID , Chuanrong Zhang 2 ID , Guifang Liu 1 , Xinyue Ye 3 and Changhong Miao 1 1
2 3
*
Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions of Ministry of Education & Collaborative Innovation Center on Yellow River Civilization of Henan Province/Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center of Urban-Rural Coordinated Development of Henan Province, Henan University, Kaifeng 475004, China; kf_guif@163.com (G.L.); chhmiao@henu.edu.cn (C.M.) Department of Geography & Center for Environmental Sciences and Engineering, University of Connecticut, Storrs, CT 06269-4148, USA; chuanrong.zhang@uconn.edu Department of Geography and Computational Social Science Lab, Kent State University, Kent, OH 44242, USA; xye5@kent.edu Correspondence: hk_lhl@163.com; Tel.: +86-0371-2388-1850
Received: 24 May 2018; Accepted: 29 June 2018; Published: 1 July 2018
Abstract: One of the side-effects generated by mainland China’s urbanization process is “ghost cities”—generally defined as clusters of abandoned buildings or housing structures—but there is a notable lack of studies on the basic characteristics related to this phenomenon, such as size, growth, level, distribution, scale, intensity, pattern and determinants. Through a combination of nighttime satellite data and daytime satellite data as a useful proxy, in this paper, we present the spatial pattern and temporal evolution of China’s ghost cities over the last two decades. Nighttime light’s rate of change in newly built areas is developed based on DMSP/OLS and Normalized Difference Built-up Index to assess a city’s darkness. Results show that the ghost city problem is real, but, at least so far, confined to 22 smaller cities. However, further analysis reveals that nighttime lights change in newly built areas, following an inverted U-curve for big cities representing a reversion from positive to negative values for the trends in recent years. The methodology through the use of the complementary characteristics in time between DMSP/OLS and Landsat data in our study prove to serve as deposing the direct evidences to ascertain and quantify such social-economic phenomenon. Keywords: nighttime satellite data; daytime satellite data; ghost cities; China; urbanization
1. Introduction Urbanization in China is of particular interest both because of the large numbers involved and because of the pace of its progress in the urban population, urban settlements and urban area. In 1978, about 195 million Chinese lived in cities; today that number approaches 700 million, with the number of cities having increased from 223 to over 660 [1–3]. Although this is a relatively low number in comparison with the average European urban population of roughly 70 to 80 percent and more than 80 percent in the United States, it is worth noting that China’s rate of urbanization took a significantly short amount of time (1978–2012) to rise from 20 percent to above 60 percent. Since the 2000s, China’s urbanization has been kicked into high gear under the “Suggestions for Making the 11th ‘Five-Year Plan” which recognized that urbanization would be an important contributing factor in the development of a balanced economy in China. The annual average growth rate has exceeded 3 percent and 30 million more people per year enter the urban population. The year 2011 Remote Sens. 2018, 10, 1037; doi:10.3390/rs10071037
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