Abstract
ABSTRACTFloating catchment area (FCA) metrics are a family of measures used to quantify spatial accessibility. Spatial accessibility fuses the concepts of accessibility and availability to describe the relationship between the supply and demand of resources. FCA metrics have been applied to measure accessibility of numerous amenities including health services, public transportation, and recreation areas. Macro-level data such as census tracts and census blocks are often used to represent population locations in the calculation of FCA metrics. This approach is susceptible to masking geographic variability that may exist at less aggregated levels, such as at the individual level. This research explores how level of data aggregation can impact the measurement and interpretation of FCA based metrics. Our case study uses the E2SFCA method to measure and compare the spatial accessibility of public parks using micro- and macro-level population representations. Our analysis shows a general agreement in the FCA results among various levels of data aggregation. As expected, error in the FCA measurements generally increased as larger areal units were used; however, our results also show a somewhat nuanced picture, as particularities arising from the Modifiable Areal Unit Problem and the gravity-based calculation of the E2SFCA appear to affect the resulting differences among FCA values. Because obtaining and using individual based data can be challenging for researchers, macro-level data are often the only reliable alternative. Our findings provide insight into the limitations associated with using macro-level data to measure and interpret spatial accessibility.
Highlights
In an ideal scenario, regardless of where people lived, they would have equal access to resources such as primary health care, healthy food options, or recreation opportunities
Regardless of where people lived, they would have equal access to resources such as primary health care, healthy food options, or recreation opportunities. Given that these resources are only available at finite locations, their distribution inevitably leads to geographic disparities within the populations they serve (Joseph and Phillips 1984), which leaves certain portions of the population with superior access and availability compared to others
The Enhanced 2SFCA (E2SFCA) outputs are mapped in Figure 1, demonstrating the variation in spatial accessibility within Alexandria and how that variation is captured at the different geographies
Summary
Regardless of where people lived, they would have equal access to resources such as primary health care, healthy food options, or recreation opportunities. Container-based regional availability measures, such as the identification of Health Professional Shortage Areas (HPSAs) and Medically Underserved Areas or Populations (MUAs/MUPs) produce physician-to-population ratios for defined service areas (i.e. county, group of counties, or portions of a county) This approach produces easy to interpret availability ratios, but distance is not accounted for within the ‘container’ and potential to access to services outside the container is not considered. To address these limitations, Luo and Wang (2003) developed the initial FCA metric called the two-step floating catchment area (2SFCA). A supply-to-demand ratio (R) is calculated by summing the population demand (P) for locations (i) that falls within the distance threshold (dij ≤ d): Rj
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