Evaluating the effectiveness of urban growth boundaries using human mobility and activity records

• We proposed a method to evaluate the effectiveness of Beijing’s UGBs using human mobility and activity records (big data).
• The research is one of the earliest attempts to use such big data to evaluate UGBs.
• The result suggested Beijing’s UGBs were quite effective in containing human activities.
• It revealed the potential underdevelopment of the public transit serving several new cities.

We proposed a methodology to evaluate the effectiveness of Beijing’s Urban Growth Boundaries (UGBs) using human mobility and activity records (big data). The research applied data from location check-in, transit smart card, taxi trajectory, and residential travel survey. We developed four types of measures to evaluate the effectives of UGBs in confining human activities and travel flows, to examine the conformity of urban activities with the planned population, and to measure the activity connections between UGBs. With the large proportions of intra- and inter-boundary travel flows and an overwhelming majority of check-ins inside the UGBs, the research concluded that Beijing’s UGBs were effective in containing human mobility and activity. However, the connections between UGBs, indicated by the spatial differentiation of the travel flows, were not consistent with the plan’s intention and strategy. It indicated the potential underdevelopment of the public transit serving several new cities.