Accessibility is the potential to interact with opportunities. Place-based measures of accessibility, such as gravity-type measures, have been widely applied to compute the opportunities accessible when traveling from a given origin and reflect aggregate geographic patterns of access across a city or region. Despite this, place-based measures are criticized for lacking a consideration of individual-level space-time constraints, which can result in inaccurate estimates of the potential for interaction at the destination, particularly due to the insufficient consideration of available time. In contrast, people-based measures rooted in time geography, such as space-time prisms (STPs), can compute both accessible opportunities and potential time to spend at each opportunity for individuals, given their travel modes and travel budgets. However, it can be difficult to represent person-based accessibility at spatially aggregate levels, limiting their application in planning practice. This study bridges place- and people-based accessibility by proposing person-based aggregate space-time accessibility (PASTA), a novel measure that starts by calculating voxel-based STPs. The discretized spatial and temporal dimensions enable further aggregations of the multidimensional arrays to return place-based measures of access whose units are measured in minutes of potential dwell time. From this, the PASTA-based approach can map potential dwell time across a city or region for many individuals or, with the incorporation of person weights, the entire population. Moreover, the aggregation can be conducted along different dimensions, making it easy to compare PASTA across space and time, as well as across travelers with different mode choices and socioeconomic characteristics. Comparisons with traditional place-based measures of market potential accessibility find positive and non-linear relationships between PASTA and gravity-type accessibility for transit and car, but more significant disparities between potential dwell time and walking and cycling access. Overall, PASTA bridges the concepts of population time and interaction potential. When paired with the underlying computational advances, this approach facilitates bringing people back into place-based accessibility analysis.
Higgins et al. (Thu,) studied this question.