Ghost Cities Analysis Based on Positioning Data in China

• DOI: 10.48550/arxiv.1510.08505
• Publication Date: 2015-01-01
• Authors: Guanghua Chi; Yü Liu; Zhengwei Wu; WU Hai-shan
• Keywords: Social and Information Networks (cs.SI); FOS: Computer and information sciences; Physics - Physics and Society; 0211 other engineering and technologies; 1. No poverty; FOS: Physical sciences; Computer Science - Social and Information Networks; 02 engineering and technology; Physics and Society (physics.soc-ph); Computer Science - Computers and Society; 11. Sustainability; Computers and Society (cs.CY)

Real estate projects are developed excessively in China this decade. Many new housing districts built, but they far exceed the actual demand some cities. These cities with a high vacancy rate called ghost The real situation of vacant areas has not been studied previous research. This study, using Baidu positioning data, presents spatial distribution and classifies large area as or tourism sites. To best our knowledge, it is first time that we detected analyzed at such fine scale. understand human dynamic cities, select one city sites cases to analyze features dynamics. study illustrates capability big data sensing objectively comprehensively.