Ghost Cities Analysis Based on Positioning Data in China

TL;DR

This paper uses Baidu positioning data to analyze the spatial distribution of ghost cities in China, providing a detailed, data-driven understanding of vacant housing areas and human dynamics in these regions.

Contribution

It is the first study to detect and analyze ghost cities in China at a fine spatial scale using big data, offering new insights into urban vacancy and human activity patterns.

Findings

Identified spatial distribution of ghost cities in China.

Classified cities and tourism sites based on vacant housing data.

Analyzed human dynamics in selected ghost cities and tourism sites.

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.