A Review of Recent Spatial Accessibility Studies That Benefitted from Advanced Geospatial Information: Multimodal Transportation and Spatiotemporal Disaggregation

Abstract

Spatial accessibility provides significant policy implications, describing the spatial disparity of access and supporting the decision-making process for placing additional infrastructure at adequate locations. Several previous reviews have covered spatial accessibility literature, focusing on empirical findings, distance decay functions, and threshold travel times. However, researchers have underexamined how spatial accessibility studies benefitted from the recently enhanced availability of dynamic variables, such as various travel times via different transportation modes and the finer temporal granularity of geospatial data in these studies. Therefore, in our review, we investigated methodological advancements in place-based accessibility measures and scrutinized two recent trends in spatial accessibility studies: multimodal spatial accessibility and temporal changes in spatial accessibility. Based on the critical review, we propose two research agendas: improving the accuracy of measurements with dynamic variable implementation and furnishing policy implications granted from the enhanced accuracy. These agendas particularly call for the action of geographers on the full implementation of dynamic variables and the strong linkage between accessibility and policymaking.

Assessing Park Accessibility Based on a Dynamic Huff Two-Step Floating Catchment Area Method and Map Service API

“…It is necessary to comprehensively analyze the accessibility of park green space from different aspects. Second, residents have limited tolerance time for different types of parks and travel modes [52]; thus, further refinement of the time threshold is required for future research [53]. Third, this paper focuses on all groups in the study area.…”

Analyzing Spatial Location Preference of Urban Activities with Mode-Dependent Accessibility Using Integrated Land Use–Transport Models

“…By taking into consideration multiple modes of transportation within populations, the multi-mode method yielded a more accurate estimate and hence provides better direction for policymakers to create cost-effective mitigation strategies. Several empirical findings, such as significant interregional and intermodal accessibility inequalities, have emerged from multimodal spatial accessibility research [13]. Most previous research employed a constant or static travel time, such as the average or peak hour travel time, to quantify accessibility, assuming that the travel time is fixed [14].…”

An Examination of the Stochastic Distribution of Spatial Accessibility to Intensive Care Unit Beds during the COVID‐19 Pandemic: A Case Study of the Greater Houston Area of Texas

“…Owing to the extraordinary outbreak of COVID‐19, the US Department of Health and Human Services ( 2020 ) estimated that 70.1% of inpatient beds (95% confidence interval [CI]: 70.2%–71.1%) and 77.9% of intensive care unit (ICU) beds (95% CI: 76.9%–78.9%) were occupied in the state of Texas as of July 14, 2020. Therefore, the limited availability of health care resources should be taken into account in spatial accessibility measurement to promote policy implications such as identification of spatial disparity or effective allocation of infrastructures (Park and Goldberg 2021 ).…”

“…As the three variables of spatial accessibility (i.e., supply, demand, and mobility) change temporally, they are subject to underlying uncertainty, which may significantly impact accessibility measurements (Park and Goldberg 2021 ). While conventional accessibility approaches (i.e., without the incorporation of uncertainty or temporal dynamics) have a tendency to exaggerate the degree of access (Kang et al 2020 ), the examination of uncertainty could provide better insights using a stochastic distribution.…”