Mobility difference index: a quantitative method for detecting human mobility difference

Differences in human mobility reflect temporal variations and spatial differences in urban spaces, including regional functions, physical environments, and geographical sentiments. Accurately quantifying these differences is critical for understanding and managing cities. However, existing measurement methods overlook the spatial distribution of population movement, which limits the ability to compare spatial differences in human mobility. Separate treatment of the spatial distribution, flux, and distance of human movement increases the complexity and uncertainty of understanding geographic phenomena. Therefore, we propose a flow-based location measure, termed the mobility difference index (MDI), that fuses multidimensional movement characteristics to quantify temporal variations and spatial differences in human mobility. The method quantifies the differences in human mobility by calculating the minimum transformation cost between two sets of origin-destination flows based on optimal transport theory. Simulation experiments confirmed the advantage of the MDI in perceiving the multidimensional characteristics of human movement, particularly regarding spatial distribution. We examined mobile signaling and positioning data from Wuhan and found that the proposed MDI could effectively identify the spatial and temporal dependencies of variations in human mobility and heterogeneous effects of spatial semantics and distance on spatial differences in human mobility.