面向轨道交通站域协同发展的交通可达与空间使用绩效关系评价——以上海中心城区为例
|
摘要
从低碳交通出行和高效空间利用的视角,关注轨道交通站域交通可达与空间使用绩效的相互影响。构建上海城市道路网络模型与轨道交通网络模型,对上海中心城区10个典型轨道交通站域的交通可达与空间使用绩效的关联性进行量化分析,在此基础上建立评价模型,提出轨交站域运用出行网络与空间使用相匹配的方法来支持城市设计决策。
From the perspective of low carbon tourism and highly efficient spatial performance, this paper concerns about the influences between urban transport accessibility and spatial performance. Shanghai road network and rail transit network were modeled to compute transport accessibilities. Based on the correlation analysis between transport accessibilities and spatial performances of 10 well-developed rail transit station areas in central Shanghai, an integrated model was developed to provide synergistic analysis method for supporting urban design decisions in rail transit station areas.
From the perspective of low carbon tourism and highly efficient spatial performance, this paper concerns about the influences between urban transport accessibility and spatial performance. Shanghai road network and rail transit network were modeled to compute transport accessibilities. Based on the correlation analysis between transport accessibilities and spatial performances of 10 well-developed rail transit station areas in central Shanghai, an integrated model was developed to provide synergistic analysis method for supporting urban design decisions in rail transit station areas.
引文
[1]张烨.图论可达性[J].建筑学报,2012(9):71-76.
[2]皮克G J.贝托里尼L,德扬H,等.透视站点地区的发展潜能:荷兰节点——场所模型的10年发展回顾[J].惠晓曦,曹浩伟,赵之枫,等译.国际城市规划,2011(6):63-71.
[3]WEGENER M, F(U|¨)RST F. Land-use Transport Interaction:Sate of the Art[EB/OL].[2017-03-05]. https://www.ssrn.com/abstract=1434678.
[4]BAJIC V. The Effects of a New Subway Line on Housing Prices in Metropolitan Toronto[J]. Urban Studies, 1983,20(2):147-158.
[5]CERVERO R. Rail Transit and Joint Development:Land marketimpacts in Washington, DC and Atlanta[J]. Journal of the American Planning Association, 1994, 60(1):83-94.
[6]郑贤,庄焰.轨道交通对沿线地价影响半径研究[J].铁道运输与经济,2007(6):45-47.
[7]潘海啸,任春洋,杨眺晕.上海轨道交通对站点地区土地使用影响的实证研究[J].城市规划学刊,2007(4):92-97.
[8]CERVERO R. Transit-based Housing in the San Francisco Bay Area:Market Profiles and Rent Premiums[J]. Transportation Quarterly, 1996, 50(3):33-49.
[9]Parsons Brinkerhoff Quade&Douglas, Inc. Transit and Urban Form(TCRP Report 16)[R]. Washington, D.C.:National Academy Press, 1996.
[10]潘海啸,刘贤腾,ZACHARIAS J,等.街区设计特征与绿色交通的选择——以上海市康健、卢湾、中原、八佰伴四个街区为例[J].城市规划汇刊,2003(6):42-48.
[11]任春洋.大都市地区轨道交通与城市中心互动耦合研究——以上海为例[D].上海:同济大学,2005.
[12]BERTOLINI L. Spatial Development Patterns and Public Transport:The Application of an Analytical Model in the Netherlands[J]. Planning Practice&Research, 1999, 14(2):199-210.
[13]索斯沃斯M.设计步行城市[J].许俊萍,译.周江评,校.国际城市规划,2012(5):54-64.
[14]PORTA S, CRUCITTI P, LATORA V. The Network Analysis of Urban Streets:A Dual Approach[J]. Physica A:Statistical Mechanics and Its Applications, 2006, 369(2):853-866.
[15]CHIARADIA A, CRISPIN C, WEBSTER C. sDNA a Software for Spatial Design Network Analysis[EB/OL].[2017-11-14].https://www.cardiff.ac.uk/sdna/.
[16]CHANG D, PENN A. Integrated Multilevel Circulation in Dense Urban Areas:The Effect of Multiple Interacting Constraints on the Use of Complex Urban Areas[J]. Environment and Planning B:Planning and Design, 1998,25(4):507-538.
[17]陆锡明,顾啸涛.上海市第五次居民出行调查与交通特征研究[J].城市交通,2011, 9(5):1-7.
(1)办公空间就业饱和率为办公楼里实际就业人数与该办公楼处于饱和容纳状态下就业人数的比值,即:实际就业人数/标准就业人数。
(2)为了消除结果的边缘效应,分析范围定为1 km,最终截取其中的500 m范围取均值。sDNA基于角度距离的可达性值角度中介性(Angular Betweenness)与人车流量有很好的相关性,因此本文所采用的可达性值均使用角度度量值。
(3)图5在统计时,工作日与周末的进店人数以5:2进行加权计算。
(4)采用SPSS的主成份分析法提取的前两个主成份可解释5个指标的83.59%。根据荷载矩阵及两个主成份的方差根,计算得到第1主成份的各系数为(0.430,0.543,0.356,0.551,-0.299),第2主成份的各系数为(-0.110,0.079,0.678,-0.032,0.720)。主成份系数分别乘以5个原始变量标准化之后的变量即为主成份的函数表达式:主成份1=0.430×Z商+0.543×Z办_1+0.356×Z办_2+0.551×Z住_1-0.299×Z住_2;主成份2=-0.110×Z商+0.079×Z办_1+0.678×Z办_2-0.032×Z住_1+0.720×Z住_2。
[2]皮克G J.贝托里尼L,德扬H,等.透视站点地区的发展潜能:荷兰节点——场所模型的10年发展回顾[J].惠晓曦,曹浩伟,赵之枫,等译.国际城市规划,2011(6):63-71.
[3]WEGENER M, F(U|¨)RST F. Land-use Transport Interaction:Sate of the Art[EB/OL].[2017-03-05]. https://www.ssrn.com/abstract=1434678.
[4]BAJIC V. The Effects of a New Subway Line on Housing Prices in Metropolitan Toronto[J]. Urban Studies, 1983,20(2):147-158.
[5]CERVERO R. Rail Transit and Joint Development:Land marketimpacts in Washington, DC and Atlanta[J]. Journal of the American Planning Association, 1994, 60(1):83-94.
[6]郑贤,庄焰.轨道交通对沿线地价影响半径研究[J].铁道运输与经济,2007(6):45-47.
[7]潘海啸,任春洋,杨眺晕.上海轨道交通对站点地区土地使用影响的实证研究[J].城市规划学刊,2007(4):92-97.
[8]CERVERO R. Transit-based Housing in the San Francisco Bay Area:Market Profiles and Rent Premiums[J]. Transportation Quarterly, 1996, 50(3):33-49.
[9]Parsons Brinkerhoff Quade&Douglas, Inc. Transit and Urban Form(TCRP Report 16)[R]. Washington, D.C.:National Academy Press, 1996.
[10]潘海啸,刘贤腾,ZACHARIAS J,等.街区设计特征与绿色交通的选择——以上海市康健、卢湾、中原、八佰伴四个街区为例[J].城市规划汇刊,2003(6):42-48.
[11]任春洋.大都市地区轨道交通与城市中心互动耦合研究——以上海为例[D].上海:同济大学,2005.
[12]BERTOLINI L. Spatial Development Patterns and Public Transport:The Application of an Analytical Model in the Netherlands[J]. Planning Practice&Research, 1999, 14(2):199-210.
[13]索斯沃斯M.设计步行城市[J].许俊萍,译.周江评,校.国际城市规划,2012(5):54-64.
[14]PORTA S, CRUCITTI P, LATORA V. The Network Analysis of Urban Streets:A Dual Approach[J]. Physica A:Statistical Mechanics and Its Applications, 2006, 369(2):853-866.
[15]CHIARADIA A, CRISPIN C, WEBSTER C. sDNA a Software for Spatial Design Network Analysis[EB/OL].[2017-11-14].https://www.cardiff.ac.uk/sdna/.
[16]CHANG D, PENN A. Integrated Multilevel Circulation in Dense Urban Areas:The Effect of Multiple Interacting Constraints on the Use of Complex Urban Areas[J]. Environment and Planning B:Planning and Design, 1998,25(4):507-538.
[17]陆锡明,顾啸涛.上海市第五次居民出行调查与交通特征研究[J].城市交通,2011, 9(5):1-7.
(1)办公空间就业饱和率为办公楼里实际就业人数与该办公楼处于饱和容纳状态下就业人数的比值,即:实际就业人数/标准就业人数。
(2)为了消除结果的边缘效应,分析范围定为1 km,最终截取其中的500 m范围取均值。sDNA基于角度距离的可达性值角度中介性(Angular Betweenness)与人车流量有很好的相关性,因此本文所采用的可达性值均使用角度度量值。
(3)图5在统计时,工作日与周末的进店人数以5:2进行加权计算。
(4)采用SPSS的主成份分析法提取的前两个主成份可解释5个指标的83.59%。根据荷载矩阵及两个主成份的方差根,计算得到第1主成份的各系数为(0.430,0.543,0.356,0.551,-0.299),第2主成份的各系数为(-0.110,0.079,0.678,-0.032,0.720)。主成份系数分别乘以5个原始变量标准化之后的变量即为主成份的函数表达式:主成份1=0.430×Z商+0.543×Z办_1+0.356×Z办_2+0.551×Z住_1-0.299×Z住_2;主成份2=-0.110×Z商+0.079×Z办_1+0.678×Z办_2-0.032×Z住_1+0.720×Z住_2。