Quantifying Barriers of Urban Mobility

TL;DR

This paper introduces a network science framework to quantify how urban barriers like roads and natural obstacles influence mobility patterns and segregation in cities, using GPS data and community detection algorithms.

Contribution

It develops a novel methodology combining GPS data, community detection, and barrier indices to empirically measure the impact of urban barriers on mobility clusters.

Findings

Barriers significantly influence the size and structure of mobility clusters.

Transportation hubs modulate the effect of barriers on mobility.

Barriers have a greater impact on residents near the city center.

Abstract

Barriers in cities, such as administrative boundaries, natural obstacles, railways or major roads are thought to induce segregation. However, the empirical knowledge about this phenomenon is limited. Here, we present a network science framework to assess barriers to urban mobility along their hierarchy, across residential areas and visited amenities. Using GPS mobility data, we construct a network of blocks from the sequence of individual stays in a major European city. A community detection algorithm allows us to partition this network into non-overlapping areas of dense mobility clusters, in which the effect of transportation hubs can be tuned with a parameter. We apply the Symmetric Area Difference index to quantify the overlap between these mobility clusters and the polygons of urban area separated by barriers. Reducing the effect of transportation hubs results in smaller scale mobility clusters that fit better to lower rank administrative or road barriers compared to their higher rank pairs. We find that characteristic urban barriers can replace each other in dividing mobility clusters of different scales. Next, we define the Barrier Crossing Ratio, the fraction of barrier crossings that bridge mobility clusters. The decomposition of this indicator by origins and destinations suggests a significantly higher impact of barriers on those who live closer to the city center and smaller impact on visits to complex amenities. These results contribute to the ongoing discourse on urban segregation, emphasizing the importance of barriers to urban mobility in shaping interactions and mixing.