References
- Boisjoly, G. and El-Geneidy, A., 2016. Daily fluctuations in transit and job availability: a comparative assessment of time-sensitive accessibility measures. Journal of Transport Geography, 52, 73–81. doi:https://doi.org/10.1016/j.jtrangeo.2016.03.004
- Chen, B.Y., et al., 2017. Measuring place-based accessibility under travel time uncertainty. International Journal of Geographical Information Science, 31 (4), 783–804. doi:https://doi.org/10.1080/13658816.2016.1238919.
- Chen, B.Y., et al., 2020. Evaluating spatial accessibility to healthcare services under travel time uncertainty: a reliability-based floating catchment area approach. Journal of Transport Geography, 87, 102794. doi:https://doi.org/10.1016/j.jtrangeo.2020.102794
- Chen, X. and Jia, P., 2019. A comparative analysis of accessibility measures by the two-step floating catchment area (2SFCA) method. International Journal of Geographical Information Science, 33 (9), 1739–1758. doi:https://doi.org/10.1080/13658816.2019.1591415.
- Dai, D., 2010. Black residential segregation, disparities in spatial access to health care facilities, and late-stage breast cancer diagnosis in metropolitan Detroit. Health and Place, 16 (5), 1038–1052. doi:https://doi.org/10.1016/j.healthplace.2010.06.012.
- Dai, D. and Wang, F., 2011. Geographic disparities in accessibility to food stores in southwest Mississippi. Environment and Planning B: Planning and Design, 38 (4), 659–677. doi:https://doi.org/10.1068/b36149.
- Delamater, P.L., 2013. Spatial accessibility in suboptimally configured health care systems: a modified two-step floating catchment area (M2SFCA) metric. Health and Place, 24, 30–43. doi:https://doi.org/10.1016/j.healthplace.2013.07.012
- Dony, C.C., Delmelle, E.M., and Delmelle, E.C., 2015. Re-conceptualizing accessibility to parks in multi-modal cities: a Variable-width floating catchment area (VFCA) method. Landscape and Urban Planning, 143, 90–99. doi:https://doi.org/10.1016/j.landurbplan.2015.06.011
- Ertugay, K. and Duzgun, S., 2011. GIS-based stochastic modeling of physical accessibility using GPS-based floating car data and Monte Carlo simulation. International Journal of Geographical Information Science, 25 (9), 1491–1506. doi:https://doi.org/10.1080/13658816.2010.528419.
- Farmer, C.J.Q., et al., 2010. Identification of snow cover regimes through spatial and temporal clustering of satellite microwave brightness temperatures. Remote Sensing of Environment, 114 (1), 199–210. doi:https://doi.org/10.1016/j.rse.2009.09.002
- Getis, A. and Ord, J.K., 1992. The analysis of spatial association by use of distance statistics. Geographical Analysis, 24 (3), 189–206. doi:https://doi.org/10.1111/j.1538-4632.1992.tb00261.x.
- Gong, S., et al., 2021. Evaluating healthcare resource inequality in Beijing, China based on an improved spatial accessibility measurement. Transactions in GIS, 25 (3), 1504–1521. doi:https://doi.org/10.1111/tgis.12737.
- Han, D. and Rogerson, P.A., 2003. Application of a GIS-based statistical method to access spatio-temporal changes in breast cancer clustering in the Northeastern United States. In: O.A. Khan and R. Skinner, eds. Geographic information systems and health applications. Hershey: IGI Global, 114–138.
- Hansen, W.G., 1959. How accessibility shapes land use. Journal of the American Institute of Planners, 25 (2), 73–76. doi:https://doi.org/10.1080/01944365908978307.
- Hu, Y. and Downs, J., 2019. Measuring and visualizing place-based space-time job accessibility. Journal of Transport Geography. doi:https://doi.org/10.1016/j.jtrangeo.2018.12.002.
- Jain, A.K., 2010. Data clustering: 50 years beyond K-means. Pattern Recognition Letters, 31 (8), 651–666. doi:https://doi.org/10.1016/j.patrec.2009.09.011.
- Järv, O., et al., 2018. Dynamic cities: location-based accessibility modelling as a function of time. Applied Geography. doi:https://doi.org/10.1016/j.apgeog.2018.04.009.
- Jia, P., Wang, F., and Xierali, I.M., 2017. Using a huff-based model to delineate hospital service areas. Professional Geographer, 69 (4), 522–530. doi:https://doi.org/10.1080/00330124.2016.1266950.
- Kang, J.Y., et al., 2020. Rapidly measuring spatial accessibility of COVID-19 healthcare resources: a case study of Illinois, USA. International Journal of Health Geographics, 19 (1), 36. doi:https://doi.org/10.1186/s12942-020-00229-x.
- Kim, Y., Byon, Y.J., and Yeo, H., 2018. Enhancing healthcare accessibility measurements using GIS: a case study in Seoul, Korea. PLoS ONE, 13, 2.
- Korea Environment Corporation, 2020. EV monitor [online]. https://www.ev.or.kr/evmonitor [Accessed 28 Nov 2020].
- Langford, M., Fry, R., and Higgs, G., 2012. Measuring transit system accessibility using a modified two-step floating catchment technique. International Journal of Geographical Information Science, 26 (2), 193–214. doi:https://doi.org/10.1080/13658816.2011.574140.
- Lee, J. and Miller, H.J., 2020. Robust accessibility: measuring accessibility based on travelers’ heterogeneous strategies for managing travel time uncertainty. Journal of Transport Geography, 86, 102747. doi:https://doi.org/10.1016/j.jtrangeo.2020.102747
- Lee, J.H., et al., 2020. Exploring electric vehicle charging patterns: mixed usage of charging infrastructure. Transportation Research Part D: Transport and Environment, 79, 102249. doi:https://doi.org/10.1016/j.trd.2020.102249
- Lee, J.H., Hardman, S.J., and Tal, G., 2019. Who is buying electric vehicles in California? Characterising early adopter heterogeneity and forecasting market diffusion. Energy Research & Social Science, 55, 218–226. doi:https://doi.org/10.1016/j.erss.2019.05.011
- Lee, W.K., Sohn, S.Y., and Heo, J., 2018. Utilizing mobile phone-based floating population data to measure the spatial accessibility to public transit. Applied Geography, 92, 123–130. doi:https://doi.org/10.1016/j.apgeog.2018.02.003
- Liu, D., Kwan, M.-P., and Kan, Z., 2021. Analysis of urban green space accessibility and distribution inequity in the city of Chicago. Urban Forestry & Urban Greening, 59, 127029. doi:https://doi.org/10.1016/j.ufug.2021.127029
- Luo, W. and Qi, Y., 2009. An enhanced two-step floating catchment area (E2SFCA) method for measuring spatial accessibility to primary care physicians. Health and Place, 15 (4), 1100–1107. doi:https://doi.org/10.1016/j.healthplace.2009.06.002.
- Luo, W. and Wang, F., 2003. Measures of spatial accessibility to health care in a GIS environment: synthesis and a case study in the Chicago region. Environment and Planning B: Planning and Design, 30 (6), 865–884. doi:https://doi.org/10.1068/b29120.
- Luo, W. and Whippo, T., 2012. Variable catchment sizes for the two-step floating catchment area (2SFCA) method. Health and Place, 18 (4), 789–795. doi:https://doi.org/10.1016/j.healthplace.2012.04.002.
- MacQueen, J., 1967. Some methods for classification and analysis of multivariate observations. In: L. Le Cam and J. Neyman, eds. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability. Berkeley: University of California, 281–297.
- Mahmoudi, M., et al., 2019. Accessibility with time and resource constraints: computing hyper-prisms for sustainable transportation planning. Computers, Environment and Urban Systems, 73, 171–183. doi:https://doi.org/10.1016/j.compenvurbsys.2018.10.002
- McGrail, M.R. and Humphreys, J.S., 2009. Measuring spatial accessibility to primary care in rural areas: improving the effectiveness of the two-step floating catchment area method. Applied Geography, 29 (4), 533–541. doi:https://doi.org/10.1016/j.apgeog.2008.12.003.
- McGrail, M.R. and Humphreys, J.S., 2014. Measuring spatial accessibility to primary health care services: utilising dynamic catchment sizes. Applied Geography, 54, 182–188. doi:https://doi.org/10.1016/j.apgeog.2014.08.005
- McLafferty, S., et al., 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. doi:https://doi.org/10.1016/j.sste.2012.02.004.
- McLafferty, S.L., 2015. Spatial mismatch. In: J.D. Wright ed. International encyclopedia of the social \& behavioral sciences: second edition. Waltham: Elsevier Inc., 157–160. doi:https://doi.org/10.1016/B978-0-08-097086-8.32193-6.
- Nathan, R.J. and McMahon, T.A., 1990. Identification of homogeneous regions for the purposes of regionalisation. Journal of Hydrology, 121 (1–4), 217–238. doi:https://doi.org/10.1016/0022-1694(90)90233-N.
- Neutens, T., 2015. Accessibility, equity and health care: review and research directions for transport geographers. Journal of Transport Geography. doi:https://doi.org/10.1016/j.jtrangeo.2014.12.006.
- Ord, J.K. and Getis, A., 1995. Local spatial autocorrelation statistics: distributional issues and an application. Geographical Analysis, 27 (4), 286–306. doi:https://doi.org/10.1111/j.1538-4632.1995.tb00912.x.
- Park, J., et al., 2017a. A study to vitalize electric vehicles through survey and analysis of the usage of owners. Sejong, South Korea: Ministry of Environment.
- Park, J. and Goldberg, D.W., 2021. A review of recent spatial accessibility studies that benefitted from advanced geospatial information: multimodal transportation and spatiotemporal disaggregation. ISPRS International Journal of Geo-Information, 10 (8), 532. doi:https://doi.org/10.3390/ijgi10080532.
- Park, K., et al., 2017b. Charging behavior analysis of electric vehicle. Journal of Korean Society of Transportation, 35 (3), 210–219. doi:https://doi.org/10.7470/jkst.2017.35.3.210.
- Rogerson, P.A., Sinha, G., and Han, D., 2006. Recent changes in the spatial pattern of prostate cancer in the U.S. American Journal of Preventive Medicine, 30 (2 SUPPL.), S50–S59. doi:https://doi.org/10.1016/j.amepre.2005.09.006.
- Rong, P., et al., 2020. Evaluation of the spatial equity of medical facilities based on improved potential model and map service API: a case study in Zhengzhou, China. Applied Geography, 119, 102192. doi:https://doi.org/10.1016/j.apgeog.2020.102192
- Rousseeuw, P.J., 1987. Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20, 53–65. doi:https://doi.org/10.1016/0377-0427(87)90125-7
- Seoul Metropolitan Government, 2020. Seoul open data plaza - floating population [online]. https://data.seoul.go.kr/dataVisual/seoul/seoulLivingPopulation.do [Accessed 28 Nov 2020].
- Shen, Q., 1998. Location characteristics of inner-city neighborhoods and employment accessibility of low-wage workers. Environment and Planning B: Planning and Design, 25 (3), 345–365. doi:https://doi.org/10.1068/b250345.
- Shin, K. and Lee, T., 2018. Improving the measurement of the Korean emergency medical System’s spatial accessibility. Applied Geography, 100, 30–38. doi:https://doi.org/10.1016/j.apgeog.2018.08.009
- Tang, J.H., et al., 2017. A flow-based statistical model integrating spatial and nonspatial dimensions to measure healthcare access. Health and Place, 47, 126–138. doi:https://doi.org/10.1016/j.healthplace.2017.08.006
- Wan, N., Zou, B., and Sternberg, T., 2012. A three-step floating catchment area method for analyzing spatial access to health services. International Journal of Geographical Information Science, 26 (6), 1073–1089. doi:https://doi.org/10.1080/13658816.2011.624987.
- Wang, F., 2020. From 2SFCA to i2SFCA: integration, derivation and validation. International Journal of Geographical Information Science, 35 (3), 628–638. doi:https://doi.org/10.1080/13658816.2020.1811868.
- Wang, J., et al., 2020. Access to hospitals: potential vs. observed. Cities, 100, 102671. doi:https://doi.org/10.1016/j.cities.2020.102671
- Wang, Y., et al., 2018. Measuring temporal variation of location-based accessibility using space-time utility perspective. Journal of Transport Geography, 73, 13–24. doi:https://doi.org/10.1016/j.jtrangeo.2018.10.002
- Ward, J.H., 1963. Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association, 58 (301), 236–244. doi:https://doi.org/10.1080/01621459.1963.10500845.
- Widener, M.J., et al., 2013. Using urban commuting data to calculate a spatiotemporal accessibility measure for food environment studies. Health & Place, 21, 1–9. doi:https://doi.org/10.1016/j.healthplace.2013.01.004
- Widener, M.J., et al., 2015. Spatiotemporal accessibility to supermarkets using public transit: an interaction potential approach in Cincinnati, Ohio. Journal of Transport Geography, 42, 72–83. doi:https://doi.org/10.1016/j.jtrangeo.2014.11.004
- Wu, X., et al., 2020. An overview of clustering methods for geo-referenced time series: from one-way clustering to co- and tri-clustering. International Journal of Geographical Information Science, 34 (9), 1822–1848. doi:https://doi.org/10.1080/13658816.2020.1726922.
- Xia, T., et al., 2019. Measuring spatio-temporal accessibility to emergency medical services through big GPS data. Health and Place, 56, 53–62. doi:https://doi.org/10.1016/j.healthplace.2019.01.012
- Xing, L., Liu, Y., and Liu, X., 2018. Measuring spatial disparity in accessibility with a multi-mode method based on park green spaces classification in Wuhan, China. Applied Geography, 94, 251–261. doi:https://doi.org/10.1016/j.apgeog.2018.03.014
- Yoo, E.H., et al., 2020. Quality of hybrid location data drawn from GPS-enabled mobile phones: does it matter? Transactions in GIS, 24 (2), 462–482. doi:https://doi.org/10.1111/tgis.12612.
- Zepp, H., Groß, L., and Inostroza, L., 2020. And the winner is? Comparing urban green space provision and accessibility in eight European metropolitan areas using a spatially explicit approach. Urban Forestry and Urban Greening, 49, 126603. doi:https://doi.org/10.1016/j.ufug.2020.126603