A comparative analysis of accessibility measures by the two-step floating catchment area (2SFCA) method

ABSTRACT

The recent decade has witnessed a new wave of development in the place-based accessibility theory, revolving around the two-step floating catchment area (2SFCA) method. The 2SFCA method, initially serving to evaluate the spatial inequity of health care services, has been further applied to other urban planning and facility access issues. Among these applications, different distance decay functions have been incorporated in the thread of model development, but their applicability and limitations have not been thoroughly examined. To this end, the paper has employed a place-based accessibility framework to compare the performance of twenty-four 2SFCA models in a comprehensive manner. Two important conclusions are drawn from this analysis: on a small analysis scale (e.g., community level), the catchment size is the most critical model component; on a large analysis scale (e.g., statewide), the distance decay function is of elevated importance. In sum, this comparative analysis provides the theoretical support necessary to the choice of the catchment size and the distance decay function in the 2SFCA method. Justification of model parameters through empirical evidence (e.g., field surveys about local travel activities) and model validation through sensitivity analysis are needed in future 2SFCA applications for various urban planning, service delivery, and spatial equity scenarios.

KEYWORDS:

• 2SFCA
• accessibility
• sensitivity analysis
• spatial interaction model
• distance decay

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The data that support the findings of this study are available in Github [https://github.com/peterbest52/2SFCA-Comparison]. These data were derived from the following resources available in the public domain: SNAP retailers database https://www.cbpp.org/snap-retailers-database and TIGER/Line with selected demographic and economic data https://www.census.gov/geo/maps-data/data/tiger-data.html

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This work was supported by the National Key R&D Program of China [2018YFC0809900].

Notes on contributors

Xiang Chen

Xiang Chen is an Assistant Professor in the Department of Emergency Management, Arkansas Tech University, USA. His research is focused on accessibility, urban food security, and environmental health.

Pengfei Jia

Pengfei Jia is a Senior Engineer in the Academy Information Center of Urban Planning, China Academy of Urban Planning and Design, China. His research is focused on big data analytics for urban planning.