基于公交服务需求与供给匹配程度的公交站点布局评价——以武汉市为例
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摘要
公交站点的布局影响了整个公交系统的运行效率与服务品质。评价或优化站点布局的文献对公交服务的供需匹配程度的关注较少。基于此不足,综合使用了密度分析和空间自相关方法来研究公交服务需求与供给的匹配程度,并以此为依据评价站点的布局情况。以武汉市主城区为例的研究结果表明:(1)整体上看:研究区域内公交服务的需求与供给匹配良好,公交站点的分布基本满足来自职住分布的需求。(2)局域上:部分公交站点的设置存在问题,对应区域存在供需失配现象,基于空间统计的方法表明,该失配现象在少部分站点所在区域相对更明显。本文中的方法可应用于公交站点布局实际案例的评估,亦可应用于相关站点布局优化方法的效果评价。
Bus stop locations may influence the efficiency and level of service of the public transport system. Estimating or optimizing stop locations requires considering the coupling level between demand and supply of bus service, which has been ignored more or less in relevant literatures. To overcame this shortcoming of existing researches, we adopted the kernel density estimation(KDE) and spatial correlation analyses to assess the bus stop placement in consideration of the coupling level between job-housing locations and bus stop locations. A case study in Wuhan, China, was carried out, which shows that:(1)From the global perspective, the layout of overall bus stops generally meets the needs coming from jobs and housing demand.(2) From the local perspective: there exist spatial mismatches between some bus stop locations and jobs and housing demands in certain area of the city, while the spatial statistical outcomes also imply that such imbalance phenomenon is more distinct on certain bus stops. The methods of this research can be used to assess either the layout of bus stops of actual cases or the outcomes of certain optimizing methods of bus systems.
Bus stop locations may influence the efficiency and level of service of the public transport system. Estimating or optimizing stop locations requires considering the coupling level between demand and supply of bus service, which has been ignored more or less in relevant literatures. To overcame this shortcoming of existing researches, we adopted the kernel density estimation(KDE) and spatial correlation analyses to assess the bus stop placement in consideration of the coupling level between job-housing locations and bus stop locations. A case study in Wuhan, China, was carried out, which shows that:(1)From the global perspective, the layout of overall bus stops generally meets the needs coming from jobs and housing demand.(2) From the local perspective: there exist spatial mismatches between some bus stop locations and jobs and housing demands in certain area of the city, while the spatial statistical outcomes also imply that such imbalance phenomenon is more distinct on certain bus stops. The methods of this research can be used to assess either the layout of bus stops of actual cases or the outcomes of certain optimizing methods of bus systems.
引文
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[17]王雪青,陈媛,刘炳胜.中国区域房地产经济发展水平空间统计分析:全局Moran's I、Moran散点图与LISA集聚图的组合研究[J].数理统计与管理,201 4;33(1):59-71.
[18]高爽,魏也华,陈雯,等.发达地区制造业集聚和水污染的空间关联:以无锡市区为例[J].地理研究,2011,30(5):902-91 2.
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[22]Kuter N,Yenilmez F,Kuter S.Forest fire risk mapping by kernel density estimation[J].Croatian Journal of Forest Engineering,201 1,32(2):599-610.
[23]Anselin L.Local indicators of spatial association--LISA[J].Geographical Analysis,1995,27(2):93-115.
[24]Anselin L.The moran scatterplot as an ESDA tool to assess local instability in spatial association:Spatial analytical perspectives on GIS[C].London:Taylor and Francis,1996:111-127.
[2]Huang Z,Zhang M,Liu X.Estimating light-rail transit peak-hour boarding based on accessibility at station and route levels in Wuhan,China[J].Transportation Planning and Technology,2017,40(5):624-639.
[3]Foda M A,Osman A 0.Using GIS for measuring transit stop accessibility considering actual pedestrian road network[J].Journal of Public Transportation,2010,13(4):23-40.
[4]Shiravi S,Zhong M,Hosseini F.Using LiDAR data for measuring transit stop coverage[J].Procedia-Social and Behavioral Sciences,2014,138:715-721.
[5]李苗裔,龙赢.中国主要城市公交站点服务范围及其空间特征评价[J].城市规划学刊,2015(6):30-37.
[6]Karner A.Assessing public transit service equity using route-level accessibility measures and public data[J].Journal of Transport Geography,2018,67:24-32.
[7]Wirasinghe S C,Ghoneim N S.Spacing of bus-stops for many to many travel demand[J].Transportation Science,1981,15(3):210-221.
[8]Li H,Bertini R L.Assessing a model for optimal bus stop spacing with highresolution archived stop-level data[J].Transportation Research Record Journal of the Transportation Research Board,2009,21 11:24-32.
[9]Murray A T.Strategic analysis of public transport coverage[J].Socio-Economic Planning Sciences,2001,35(3):175-188.
[10]Murray A T.A coverage model for improving public transit systemaccessibility and expanding access[J].Annals of Operations Research,2003,123(1-4):143-156.
[11]Murray A T,Wu X.Accessibility tradeoffs in public transit planning[J].Journal of Geographical Systems,2003,5(1):93-107.
[12]Sha A M,Lownes N E.Access and connectivity trade-offs in transit stop location[J].Transportation Research Record Journal of the Transportation Research Board,2014,2466:1-11.
[13]Lwin K,Murayama Y.A GIS approach to estimation of building population for micro-spatial analysis[J].Transactions in GIS,2009,13(4):401-414.
[14]Zhang Z,Feng Z,Zhang H,et al.Spatial distribution of grassland fires at the regional scale based on the MODIS active fire products[J].International Journal of Wildland Fire,201 7,26(3):209.
[15]禹文豪,艾廷华,杨敏,等.利用核密度与空间自相关进行城市设施兴趣点分布热点探测[J].武汉大学学报(信息科学版),201 6,41(2):221-227.
[16]Xie Z,Yan J.Detecting traffic accident clusters with network kernel density estimation and local spatial statistics:an integrated approach[J].Journal of Transport Geography,201 3,31:64-71.
[17]王雪青,陈媛,刘炳胜.中国区域房地产经济发展水平空间统计分析:全局Moran's I、Moran散点图与LISA集聚图的组合研究[J].数理统计与管理,201 4;33(1):59-71.
[18]高爽,魏也华,陈雯,等.发达地区制造业集聚和水污染的空间关联:以无锡市区为例[J].地理研究,2011,30(5):902-91 2.
[19]Silverman B W.Density Estimation for Statistics and Data Analysis[M].London:Chapman and Hall,1986.
[20]Gatrell A C,Bailey T C,Diggle P J,etal.Spatial point pattern analysis and its application in geographical epidemiology[J].Transactions of the Institute of British Geographers,1196,21(l):256-274.
[21]Guo F,Innes J L,Wang G,et al.Historic distribution and driving factors of humancaused fires in the Chinese boreal forest between 1972 and 2005[J].Journal of Plant Ecology,2015,8(5):480-490.
[22]Kuter N,Yenilmez F,Kuter S.Forest fire risk mapping by kernel density estimation[J].Croatian Journal of Forest Engineering,201 1,32(2):599-610.
[23]Anselin L.Local indicators of spatial association--LISA[J].Geographical Analysis,1995,27(2):93-115.
[24]Anselin L.The moran scatterplot as an ESDA tool to assess local instability in spatial association:Spatial analytical perspectives on GIS[C].London:Taylor and Francis,1996:111-127.