References
- Allen, J., & Farber, S. (2020). A measure of competitive access to destinations for comparing across multiple study regions. Geographical Analysis, 52(1), 69–86. https://doi.org/https://doi.org/10.1111/gean.12188
- Apparicio, P., Gelb, J., Dubé, A.-S., Kingham, S., Gauvin, L., & Robitaille, É. (2017). The approaches to measuring the potential spatial access to urban health services revisited: Distance types and aggregation-error issues. International Journal of Health Geographics, 16(1), 32. https://doi.org/https://doi.org/10.1186/s12942-017-0105-9
- Arsanjani, J. J., Zipf, A., Mooney, P., & Helbich, M. (2015). OpenStreetMap in GIScience. Lecture Notes in Geoinformation and Cartography. Springer, Cham.
- Benenson, I., Martens, K., Rofé, Y., & Kwartler, A. (2011). Public transport versus private car GIS-based estimation of accessibility applied to the Tel Aviv metropolitan area. Annals of Regional Science, 47(3), 499–515. https://doi.org/https://doi.org/10.1007/s00168-010-0392-6
- Brovelli, M. A., Minghini, M., Molinari, M., & Mooney, P. (2017). Towards an automated comparison of OpenStreetMap with authoritative road datasets. Transactions in GIS, 21(2), 191–206. https://doi.org/https://doi.org/10.1111/tgis.12182
- Center for Medicare & Medicaid Services. (2017). NPI lookup—get the NPI number of doctors & physicians. Baltimore, MD: U.S. Centers for Medicare & Medicaid Services.
- Center for Workforce Studies. (2011, November). 2011 state physician workforce data book. Workforce.
- Chen, B. Y., Yuan, H., Li, Q., Wang, D., Shaw, S.-L., Chen, H.-P., & Lam, W. H. K. (2017). Measuring place-based accessibility under travel time uncertainty. International Journal of Geographical Information Science, 31(4), 783–804. https://doi.org/https://doi.org/10.1080/13658816.2016.1238919
- Delamater, P. L. (2013). Spatial accessibility in suboptimally configured health care systems: A modified two-step floating catchment area (M2SFCA) metric. Health & Place, 24, 30–43. https://doi.org/https://doi.org/10.1016/j.healthplace.2013.07.012
- Delamater, P. L., Messina, J. P., Shortridge, A. M., & Grady, S. C. (2012). Measuring geographic access to health care: Raster and network-based methods. International Journal of Health Geographics, 11(1), 15. https://doi.org/https://doi.org/10.1186/1476-072X-11-15
- Delmelle, E. M., Cassell, C. H., 2, Dony, C., 1, Radcliff, E., 3, Tanner, J. P., 4, Siffel, C., 2, & Kirby, R. S. (2013). Modeling travel impedance to medical care for children with birth defects using geographic information systems. Birth Defects Research Part A, Clinical and Molecular Teratology, 97(10), 673–684. https://doi.org/https://doi.org/10.1126/science.1249098.Sleep
- Delmelle, E. M., Marsh, D. M., Dony, C., & Delamater, P. L. (2019). Travel impedance agreement among online road network data providers. International Journal of Geographical Information Science, 33(6), 1251–1269. https://doi.org/https://doi.org/10.1080/13658816.2018.1557662
- ESRI. (2006). About streetMap USA data. http://webhelp.esri.com/arcgisdesktop/9.2/body.cfm?tocVisable=1&ID=5799&TopicName=AboutStreetMapUSAdata
- ESRI. (2015). More accurate geocoding and routing with StreetMap premium. https://www.esri.com/about/newsroom/arcnews/more-accurate-geocoding-and-routing-with-streetmap-premium/
- ESRI. (2019a). Add GTFS to a network dataset user’s guide. https://github.com/Esri/public-transit-tools/blob/master/add-GTFS-to-a-network-dataset/UsersGuide.md
- ESRI. (2019b). ArcGIS online logistics services. https://logistics.arcgis.com/arcgis/rest/services
- ESRI. (2019c). What is ArcGIS StreetMap premium?—ArcGIS StreetMap Premium | Documentation. https://doc.arcgis.com/en/streetmap-premium/get-started/overview.htm
- Fisher, P., Comber, A., & Wadsworth, R. (2006). Approaches to uncertainty in spatial data. In R. Devillers & R. Jeansoulin (Ed.), Fundamentals of Spatial Data Quality (pp. 43–59). ISTE Publishing Company.
- Frizzelle, B. G., Evenson, K. R., Rodriguez, D. A., & Laraia, B. A. (2009). The importance of accurate road data for spatial applications in public health: Customizing a road network. International Journal of Health Geographics, 8(1), 24. https://doi.org/https://doi.org/10.1186/1476-072X-8-24
- Golub, A., & Martens, K. (2014). Using principles of justice to assess the modal equity of regional transportation plans. Journal of Transport Geography, 41, 10–20. https://doi.org/https://doi.org/10.1016/j.jtrangeo.2014.07.014
- Goodchild, M. (1998). Uncertainty: The Achilles heel of GIS? Geo Info Systems, 50–52. http://www.geog.ucsb.edu/~good/papers/293.pdf
- Google Maps. (2019). Distance matrix API get started. https://developers.google.com/maps/documentation/distance-matrix/intro
- Graser, A., Straub, M., & Dragaschnig, M. (2014). Towards an open source analysis toolbox for street network comparison: Indicators, tools and results of a comparison of OSM and the official A ustrian reference graph. Transactions in GIS, 18(4), 510–526. https://doi.org/https://doi.org/10.1111/tgis.12061
- Hashemi, P., & Ali Abbaspour, R. (2015). Assessment of logical consistency in OpenStreetMap based on the spatial similarity concept. In J. Jokar Arsanjani, A. Zipf, P. Mooney, & M. Helbich (Eds.), OpenStreetMap in giscience: Experiences, research, and applications (pp. 19–36). Springer International Publishing. https://doi.org/https://doi.org/10.1007/978-3-319-14280-7_2
- Hawbaker, T. J., & Radeloff, V. C. (2004). Roads and landscape pattern in northern Wisconsin based on a comparison of four road data sources. Conservation Biology, 18(5), 1233–1244. https://doi.org/https://doi.org/10.1111/j.1523-1739.2004.00231.x
- Hu, Y., Wang, C., Li, R., & Wang, F. (2020). Estimating a large drive time matrix between ZIP codes in the United States: A differential sampling approach. Journal of Transport Geography, 86(June), 102770. https://doi.org/https://doi.org/10.1016/j.jtrangeo.2020.102770
- Huber, S., & Rust, C. (2016). Calculate travel time and distance with openstreetmap data using the open source routing machine (OSRM). The Stata Journal: Promoting Communications on Statistics and Stata, 16(2), 416–423. https://doi.org/https://doi.org/10.1177/1536867X1601600209
- Infogroup. (2016). Family practice physicians in New Mexico.
- Intezari, A., & Gressel, S. (2017). Information and reformation in KM systems: Big data and strategic decision-making. Journal of Knowledge Management, 21(1), 71–91. https://doi.org/https://doi.org/10.1108/JKM-07-2015-0293
- Kirby, R. S., Delmelle, E., & Eberth, J. M. (2017). Advances in spatial epidemiology and geographic information systems. Annals of Epidemiology, 27(1), 1–9. https://doi.org/https://doi.org/10.1016/j.annepidem.2016.12.001
- Kwan, M.-P. (2012). The Uncertain Geographic Context Problem. Annals of the Association of American Geographers, 102(5), 958–968. https://doi.org/https://doi.org/10.1080/00045608.2012.687349
- Langford, M., Higgs, G., & Fry, R. (2016). Multi-modal two-step floating catchment area analysis of primary health care accessibility. Health & Place, 38, 70–81. https://doi.org/https://doi.org/10.1016/j.healthplace.2015.11.007
- Lin, Y., Wan, N., Sheets, S., Gong, X., & Davies, A. (2018). A multi-modal relative spatial access assessment approach to measure spatial accessibility to primary care providers. International Journal of Health Geographics, 17(1), 1–22. https://doi.org/https://doi.org/10.1186/s12942-018-0153-9
- Luo, W., & Qi, Y. (2009). An enhanced two-step floating catchment area (E2SFCA) method for measuring spatial accessibility to primary care physicians. Health & Place, 15(4), 1100–1107. https://doi.org/https://doi.org/10.1016/j.healthplace.2009.06.002
- Mao, L., & Nekorchuk, D. (2013). Measuring spatial accessibility to healthcare for populations with multiple transportation modes. Health & Place, 24, 115–122. https://doi.org/https://doi.org/10.1016/j.healthplace.2013.08.008
- McLafferty, S., Freeman, V. L., Barrett, R. E., Luo, L., & Shockley, A. (2012). Spatial error in geocoding physician location data from the AMA Physician Masterfile: Implications for spatial accessibility analysis. Spatial and Spatio-Temporal Epidemiology, 3(1), 31–38. https://doi.org/https://doi.org/10.1016/j.sste.2012.02.004
- Mooney, P., & Minghini, M. (2017). A review of OpenStreetMap data. In G. Foody, L. See, S. Fritz, P. Mooney, A.-M. Olteanu-Raimond, C. C. Fonte, & V. Antoniou (Eds.), Mapping and the Citizen sensor (pp. 37–59). Ubiquity Press.
- Paez, A., Higgins, C. D., & Vivona, S. F. (2019). Demand and level of service inflation in Floating Catchment Area (FCA) methods. PLoS ONE, 14(6), e0218773. https://doi.org/https://doi.org/10.1371/journal.pone.0218773
- Páez, A., Mercado, R. G., Farber, S., Morency, C., & Roorda, M. (2010). Relative accessibility deprivation indicators for urban settings: Definitions and application to food deserts in montreal. Urban Studies, 47(7), 1415–1438. https://doi.org/https://doi.org/10.1177/0042098009353626
- Pedigo, A. S., & Odoi, A. (2010). Investigation of disparities in geographic accessibility to emergency stroke and myocardial infarction care in East Tennessee using geographic information systems and network analysis. Annals of Epidemiology, 20(12), 924–930. https://doi.org/https://doi.org/10.1016/j.annepidem.2010.06.013
- Touya, G., & Reimer, A. (2015). Inferring the scale of OpenStreetMap features. In J. J. Arsanjani, A. Zipf, P. Mooney, & M. Helbich (Eds.), OpenStreetMap in GIScience: Experiences, research, and applications (pp. 81–99). Springer International Publishing. https://doi.org/https://doi.org/10.1007/978-3-319-14280-7_5
- Transitfeeds. (2017). ABQ ride GTFS.
- U.S. Census Bureau. (2018). TIGER/Line Shapefiles. https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html
- U.S. Census Bureau. (n.d.). U.S. census bureau QuickFacts: Albuquerque city, New Mexico. Retrieved May 27, 2021, from https://www.census.gov/quickfacts/albuquerquecitynewmexico
- Wan, N., Zhan, F. B., Zou, B., & Chow, E. (2012). A relative spatial access assessment approach for analyzing potential spatial access to colorectal cancer services in Texas. Applied Geography, 32(2), 291–299. https://doi.org/https://doi.org/10.1016/j.apgeog.2011.05.001
- Wang, F. (2017). Quantitative methods and socio-economic applications in GIS (2nd ed.). CRC Press, Inc.
- Wang, F, & Xu, Y. (2011). Estimating O-D travel time matrix by Google Maps API: Implementation, advantages, and implications. Annals of GIS, 17(4), 199–209. https://doi.org/https://doi.org/10.1080/19475683.2011.625977
- Weiss, D. J., Nelson, A., Gibson, H. S., Temperley, W., Peedell, S., Lieber, A., Hancher, M., Poyart, E., Belchior, S., Fullman, N., Mappin, B., Dalrymple, U., Rozier, J., Lucas, T. C. D., Howes, R. E., Tusting, L. S., Kang, S. Y., Cameron, E., Bisanzio, D., Bhatt, S., & Gething, P. W. (2018). A global map of travel time to cities to assess inequalities in accessibility in 2015. Nature, 553(7688), 333–336. https://doi.org/https://doi.org/10.1038/nature25181