Authors: Yan Lin*, Department of Geography & Environmental Studies, University of New Mexico, Sagert Sheets, Mid-Region Metropolitan Planning Organization, Mid-Region Council of Governments (New Mexico), Angela Davies, Department of Geography & Environmental Studies, University of New Mexico
Topics: Geographic Information Science and Systems, Spatial Analysis & Modeling, Medical and Health Geography
Keywords: Uncertainty; 2SFCA; multimodal; spatial access; healthcare; Street network
Session Type: Paper
Start / End Time: 8:00 AM / 9:40 AM
Room: Marshall South, Marriott, Mezzanine Level
Presentation File: No File Uploaded
Two-step floating catchment area (2SFCA) methods that account for multiple transportation modes provide more realistic accessibility representations than single-mode methods. However, uncertainties in measures of spatial access to health care are often generated by differences in data sources and scales, then propagated and amplified throughout the analysis and modeling process. This study examined how uncertainty is generated by differences in street network data and by differences in the impedance coefficient in an impedance function using a multi-modal 2SFCA method. An empirical study on spatial access to primary care physicians in the city of Albuquerque, NM, USA was conducted to evaluate the uncertainty. We used four different street network datasets (ESRI North America Detailed Streets, ESRI StreetMap Premium, streets from New Mexico’s Mid-Region Council of Governments, and OpenStreetMap) to calculate travel time by car. We used General Transit Specification Feed (GTFS) data in conjunction with the above four street datasets to calculate the travel time by bus. In order to observe the uncertainty in the output of multi-modal 2SFCA model, we applied multiple combinations of impedance coefficients in the model for each street network. We then evaluated the sensitivity of spatial access scores for car drivers, bus riders, and both cohorts to changes in street network data sources and the model parameters. Results from this study suggest researchers should use caution in selecting street data sources and model parameters, considering that the choices may alter the spatial accessibility results.