Uncovering New Insights into Green Space Accessibility with Mobile Location Data

Accessibility to urban green spaces is recognized to have wide-ranging benefits for population health. Yet, the ways in which green space accessibility is quantified remain limited, with popular approaches based on measuring the spatial distribution of opportunities with respects to population locations. These measures cannot consider real and lived human interactions with green spaces and therefore theorize the accessibility potential of populations. With the advent of mobile location data derived from GPS-enabled devices, it has become possible to quantify accessibility from an alternative, behavior-based perspective that is rooted in actual interactions with green spaces. Here, we present a comprehensive analysis of green space accessibility in two U.S. cities, Santa Barbara and New Haven, implementing a multidimensional framework that enables a comparison between potential accessibility and the actual access patterns of populations. In doing so, we compute six unique accessibility measures and composite scores of potential and actual accessibility. Our analysis reveals that, in most neighborhoods, measures of potential accessibility are aligned with actual visitation patterns, although a sizable proportion exhibit contrasting levels of potential and actual accessibility. We find that, at the neighborhood level, specific combinations of potential and actual accessibility are associated with sociodemographic characteristics. Collectively, our analyses demonstrate the value of quantifying accessibility from multiple perspectives and measures. Human-mobility-derived accessibility measures serve to provide fundamental new insights into green space accessibility, uncovering nuanced spatial distributions and distinctions based on the sociodemographic compositions of neighborhoods.