Ghost Cities Analysis Based on Positioning Data in China
October 28, 2015 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Guanghua Chi, Yu Liu, Zhengwei Wu, Haishan Wu
arXiv ID
1510.08505
Category
cs.SI: Social & Info Networks
Cross-listed
cs.CY,
physics.soc-ph
Citations
50
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Real estate projects are developed excessively in China in this decade. Many new housing districts are built, but they far exceed the actual demand in some cities. These cities with a high housing vacancy rate are called ghost cities. The real situation of vacant housing areas in China has not been studied in previous research. This study, using Baidu positioning data, presents the spatial distribution of the vacant housing areas in China and classifies cities with a large vacant housing area as cities or tourism sites. To the best of our knowledge, it is the first time that we detected and analyzed the ghost cities in China at such fine scale. To understand the human dynamic in ghost cities, we select one city and one tourism sites as cases to analyze the features of human dynamics. This study illustrates the capability of big data in sensing our cities objectively and comprehensively.
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