Mobility Census for the analysis of rapid urban development

Abstract

Traditionally urban structure and development are monitored using infrequent high-quality datasets such as censuses. However, human culture is accelerating and aggregating, leading to ever-larger cities and an increased pace of urban development. Our modern interconnected world also provides us with new data sources that can be leveraged in the study of cities. However, these often noisy and unstructured sources of big data pose new challenges. Here we propose a method to extract meaningful explanatory variables and classifications from such data. Using movement data from Beijing, which is produced as a byproduct of mobile communication, we show that meaningful features can be extracted, revealing for example the emergence and absorption of subcenters. In the future this method will allow the analysis of urban dynamics at a high spatial resolution (here, 500m) and near real-time frequency