[1] Anselin L, Bera A K, Florax R et al., 1996. Simple diagnostic tests for spatial dependence. Regional Science and Urban Economics, 26(1):77-104. doi:10.1016/0166-0462(95) 02111-6
[2] Blainey S P, Preston J M, 2013. Extending geographically weighted regression from points to flows:a rail-based case study. Proceedings of the Institution of Mechanical Engineers, Part F:Journal of Rail and Rapid Transit, 227(6):724-734. doi: 10.1177/0954409713496987
[3] Cardozo O D, García-Palomares J C, Gutiérrez J, 2012. Applica-tion of geographically weighted regression to the direct fore-casting of transit ridership at station-level. Applied Geography, 34:548-558. doi: 10.1016/j.apgeog.2012.01.005
[4] Cervero R, Ferrell C, Murphy S, 2002. Transit-Oriented Devel-opment and Joint Development in the United States:A Litera-ture Review. Washington, DC:Transportation Research Board.
[5] Chan S, Miranda-Moreno L, 2013. A station-level ridership model for the metro network in Montreal, Quebec. Canadian Journal of Civil Engineering, 40(3):254-262. doi: 10.1139/cjce-2011-0432
[6] Choi J, Lee Y J, Kim T et al., 2012. An analysis of Metro ridership at the station-to-station level in Seoul. Transportation, 39(3):705-722. doi: 10.1007/s11116-011-9368-3
[7] Dill J, Schlossberg M, Ma L et al., 2013. Predicting Transit Rid-ership at the Stop Level:the Role of Service and Urban Form. Washington, DC:Transportation Research Board.
[8] Durning M, Townsend C, 2015. Direct ridership model of rail rapid transit systems in Canada. Transportation Research Record:Journal of the Transportation Research Board, 2537(1):96-102. doi: 10.3141/2537-11
[9] Estupiñán N, Rodríguez D A, 2008. The relationship between urban form and station boardings for Bogota's BRT. Trans-portation Research Part A:Policy and Practice, 42(2):296-306. doi: 10.1016/j.tra.2007.10.006
[10] Fotheringham A S, Brunsdon C, Charlton M E, 2003. Geograph-ically Weighted Regression:the Analysis of Spatially Varying Relationships. Chichester:Wiley.
[11] Gan Z, Yang M, Feng T et al., 2018. Understanding urban mobility patterns from a spatiotemporal perspective:daily ridership profiles of metro stations. Transportation. doi: 10.1007/s11116-018-9885-4
[12] Guerra E, Cervero R, Tischler D, 2012. Half-mile circle:does it best represent transit station catchments? Transportation Re-search Record:Journal of the Transportation Research Board, 2276(1):101-109. doi: 10.3141/2276-12
[13] Gutiérrez J, Cardozo O D, García-Palomares J C, 2011. Transit ridership forecasting at station level:an approach based on dis-tance-decay weighted regression. Journal of Transport Geogra-phy, 19(6):1081-1092. doi: 10.1016/j.jtrangeo.2011.05.004
[14] Jun M J, Choi K, Jeong J E et al., 2015. Land use characteristics of subway catchment areas and their influence on subway rid-ership in Seoul. Journal of Transport Geography, 48:30-40. doi: 10.1016/j.jtrangeo.2015.08.002
[15] Kepaptsoglou K, Stathopoulos A, Karlaftis M G, 2017. Ridership estimation of a new LRT system:direct demand model ap-proach. Journal of Transport Geography, 58:146-156. doi: 10.1016/j.jtrangeo.2016.12.004
[16] Kim D, Ahn Y, Choi S et al., 2016. Sustainable mobility:longitu-dinal analysis of built environment on transit ridership. Sus-tainability, 8(10):1016. doi: 10.3390/su8101016
[17] Kuby M, Barranda A, Upchurch C, 2004. Factors influencing light-rail station boardings in the United States. Transportation Research Part A:Policy and Practice, 38(3):223-247. doi: 10.1016/j.tra.2003.10.006
[18] Lloyd C, Shuttleworth I, 2005. Analysing commuting using local regression techniques:scale, sensitivity, and geographical pat-terning. Environment and Planning A:Economy and Space, 37(1):81-103. doi: 10.1068/a36116
[19] Loo B P Y, Chen C, Chan E T H, 2010. Rail-based transit-oriented development:lessons from New York City and Hong Kong. Landscape and Urban Planning, 97(3):202-212. doi: 10.1016/j.landurbplan.2010.06.002
[20] Macdonald-Wallis K, Jago R, Page A S et al., 2011. School-based friendship networks and children's physical activity:a spatial analytical approach. Social Science & Medicine, 73(1):6-12. doi: 10.1016/j.socscimed.2011.04.018
[21] Mason R L, Gunst R F, Hess J L, 1989. Statistical Design and Analysis of Experiments:with Applications to Engineering and Science. New York:Wiley.
[22] McNally M G, 2007. The four-step model. In:Hensher D A, But-ton K J (eds). Handbook of Transport Modelling. Oxford:Pergamon, 35-53.
[23] Ministry of Housing and Urban-Rural Development, 2012. Guidelines for Planning and Design of Urban Rail. Beijing:China Construction Industry Publishing House. (in Chinese)
[24] Páez A, 2006. Exploring contextual variations in land use and transport analysis using a probit model with geographical weights. Journal of Transport Geography, 14(3):167-176. doi: 10.1016/j.jtrangeo.2005.11.002
[25] Pavlyuk D, 2016. Implication of spatial heterogeneity for airports' efficiency estimation. Research in Transportation Economics, 56:15-24. doi: 10.1016/j.retrec.2016.07.002
[26] Pulugurtha S S, Agurla M, 2012. Assessment of models to esti-mate bus-stop level transit ridership using spatial modeling methods. Journal of Public Transportation, 15(1):33-52. doi: 10.5038/2375-0901.15.1.3
[27] Rasouli S, Timmermans H, 2014. Activity-based models of travel demand:promises, progress and prospects. International Journal of Urban Sciences, 18(1):31-60. doi: 10.1080/12265934.2013.835118
[28] Ryan S, Frank L F, 2009. Pedestrian environments and transit ridership. Journal of Public Transportation, 12(1):39-57. doi: 10.5038/2375-0901.12.1.3
[29] Sohn K, Shim H, 2010. Factors generating boardings at metro stations in the Seoul metropolitan area. Cities, 27(5):358-368. doi: 10.1016/j.cities.2010.05.001
[30] Sung H, Oh J T, 2011. Transit-oriented development in a high-density city:identifying its association with transit rid-ership in Seoul, Korea. Cities, 28(1):70-82. doi: 10.1016/j.cities.2010.09.004
[31] Tobler W R, 1970. A computer movie simulating urban growth in the Detroit region. Economic Geography, 46(S1):234-240.
[32] Zhang D P, Wang X K, 2014. Transit ridership estimation with network Kriging:a case study of Second Avenue Subway, NYC. Journal of Transport Geography, 41:107-115. doi: 10.1016/j.jtrangeo.2014.08.021
[33] Zhao J B, Deng W, Song Y et al., 2013. What influences metro station ridership in China? Insights from Nanjing. Cities, 35:114-124. doi: 10.1016/j.cities.2013.07.002
[34] Zhao J B, Deng W, Song Y et al., 2014. Analysis of Metro rid-ership at station level and station-to-station level in Nanjing:an approach based on direct demand models. Transportation, 41(1):133-155. doi: 10.1007/s11116-013-9492-3