基于出行大数据的苏州村镇空间可达性及优化策略
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摘要
"村—镇—城"之间良好的交通可达性是地区"在地"城镇化的重要支撑。文章以苏州为例,通过采集实时出行大数据作为可达性测度指标,运用ArcG IS等值线空间分析方法,分析城乡交通一体化下村镇空间可达性的新水平与新特征。研究表明,苏州"村—镇""镇—城""村—城"已形成"20—40—60"分钟的小汽车三圈层格局,建构了城乡1小时时空圈,但在城镇化的驱动、自然地形的限制及地理区位的影响等因素共同作用下,可达性表现出显著的时空差异特征;公共交通可达性水平远滞后于小汽车,形成2.5小时时空圈,可达性高低的空间分布则与城镇空间发展"双轴"格局密切相关。文章结合不同村镇可达性的特点,因地制宜地提出改善区域道路网络结构、创新公共交通多元发展和调整村镇布局等规划优化策略。
Fluent traffic between village, town, and city is important in supporting in-situ urbanization. With Suzhou as an example,the paper collects instantaneous outgoing big data as measurement indices, uses ArcGIS analysis method, studies the new level and character of town space accessibility in integrated urban rural transport system. The result shows that Suzhou has developed 20 minute village-town, 40 minute town-city, 60 minute village-city traffic circles. Under the influence of urbanization,natural topography, and geographical location, the accessibility has distinctive space-temporal difference. Public transport is lagging far behind cars by 2.5 hour traffic circle. Its spatial distribution is closely related to bi-axial urban layout. The paper puts forwards improvement strategies in regional road network, public transportation, village and town layout.
Fluent traffic between village, town, and city is important in supporting in-situ urbanization. With Suzhou as an example,the paper collects instantaneous outgoing big data as measurement indices, uses ArcGIS analysis method, studies the new level and character of town space accessibility in integrated urban rural transport system. The result shows that Suzhou has developed 20 minute village-town, 40 minute town-city, 60 minute village-city traffic circles. Under the influence of urbanization,natural topography, and geographical location, the accessibility has distinctive space-temporal difference. Public transport is lagging far behind cars by 2.5 hour traffic circle. Its spatial distribution is closely related to bi-axial urban layout. The paper puts forwards improvement strategies in regional road network, public transportation, village and town layout.
引文
[1]J G Koenig. Indicators of Urban Accessi-bility:Theory and Appli-cation[J]. Transportation, 1980(2):145-172.
[2]李平华,陆玉麒.可达性研究的回顾与展望[J].地理科学进展,2005(3):69-78.
[3]Walter G Hansen. How Accessibility Shapes Land Use[J]. Journal of the American Planning Association, 1959(2):73-76.
[4]Mei-Po Kwan. Gender and Individual Access to Urban Opportunities:A Study Using Space-time Measures[J]. The Professional Geographer, 1999(2):210-227.
[5]曹小曙,李涛,杨文越,等.基于陆路交通的丝绸之路经济带可达性与城市空间联系[J].地理科学进展,2015(6):657-664.
[6]钟业喜,黄洁,文玉钊.高铁对中国城市可达性格局的影响分析[J].地理科学,2015(4):387-395.
[7]于茜,白建军,张晶言,等.路网通达性与城镇空间扩展的耦合关系—以西安市为例[J].经济地理,2016(10):69-75.
[8]宋明洁,王宏志,邵奇慧,等.小城镇可达性及其与农村聚落空间格局的关系—以荆州市93个小城镇为例[J].人文地理,2013(5):54-60.
[9]K Ozbay,D Ozmen,J Berechman. Modeling and Analysis of the Link be-tween Accessibility and Employment Growth[J]. Journal of Transportation Engineering, 2006(5):385-353.
[10]吕斌,张纯,陈天鸣.城市低收入群体的就业可达性变化研究—以北京为例[J].城市规划,2013(1):56-63.
[11]俞孔坚,段铁武,李迪华,等.景观可达性作为衡量城市绿地系统功能指标的评价方法与案例[J].城市规划,1999(8):7-10,42,63.
[12]马琳,陆玉麒.基于路网结构的城市绿地景观可达性研究—以南京市主城区公园绿地为例[J].中国园林,2011(7):92-96.
[13]宋小冬,钮心毅.再论居民出行可达性的计算机辅助评价[J].城市规划汇刊,2000(3):18-22,75-79.
[14]Kwan M-P, Murray A T, O’Kelly M E.et al. Recent Advances in Accessibility Research:Representation, Methodology and Applications[J].Journal of Geographical Systems, 2003(5):129-138.
[15]程昌秀,张文尝,陈洁,等.基于空间句法的地铁可达性评价分析—以2008年北京地铁规划图为例[J].地球信息科学,2007(6):31-35.
[16]丁亮,钮心毅,宋小冬.基于移动定位大数据的城市空间研究进展[J].国际城市规划,2015(4):53-58.
[17]曹阳,甄峰.居民住区活动特征识别及影响因素研究[J].规划师,2017(2):124-130.
[18]秦萧,甄峰,熊丽芳,等.大数据时代城市时空间行为研究方法[J].地理科学进展,2013(9):1 352-1 361.
(1)交通运行指数(又称“交通拥堵指数”,Traffic Performance Index,简称“TPI”),即用量化方法表达道路交通运行拥堵程度,是道路交通状态的数字化表达。苏州的交通运行指数大数据几乎覆盖了苏州市区内所有道路,交通指数用介于0~100的数值表达,数值越大表明道路交通越拥堵,数值越小表明交通越畅通。
(2)最大波动幅度指高峰期最长可达性时间与非高峰期最短可达性时间的比值。
(3)“微循环公交”是随着城市与交通规划的不断发展,越来越多的城市区域或社区难以被公共交通有效覆盖,居民居住点或活动区域远离公交、地铁等公共交通站点,由此应运而生的一种乘客“最后一公里”的公共交通解决方案。
[2]李平华,陆玉麒.可达性研究的回顾与展望[J].地理科学进展,2005(3):69-78.
[3]Walter G Hansen. How Accessibility Shapes Land Use[J]. Journal of the American Planning Association, 1959(2):73-76.
[4]Mei-Po Kwan. Gender and Individual Access to Urban Opportunities:A Study Using Space-time Measures[J]. The Professional Geographer, 1999(2):210-227.
[5]曹小曙,李涛,杨文越,等.基于陆路交通的丝绸之路经济带可达性与城市空间联系[J].地理科学进展,2015(6):657-664.
[6]钟业喜,黄洁,文玉钊.高铁对中国城市可达性格局的影响分析[J].地理科学,2015(4):387-395.
[7]于茜,白建军,张晶言,等.路网通达性与城镇空间扩展的耦合关系—以西安市为例[J].经济地理,2016(10):69-75.
[8]宋明洁,王宏志,邵奇慧,等.小城镇可达性及其与农村聚落空间格局的关系—以荆州市93个小城镇为例[J].人文地理,2013(5):54-60.
[9]K Ozbay,D Ozmen,J Berechman. Modeling and Analysis of the Link be-tween Accessibility and Employment Growth[J]. Journal of Transportation Engineering, 2006(5):385-353.
[10]吕斌,张纯,陈天鸣.城市低收入群体的就业可达性变化研究—以北京为例[J].城市规划,2013(1):56-63.
[11]俞孔坚,段铁武,李迪华,等.景观可达性作为衡量城市绿地系统功能指标的评价方法与案例[J].城市规划,1999(8):7-10,42,63.
[12]马琳,陆玉麒.基于路网结构的城市绿地景观可达性研究—以南京市主城区公园绿地为例[J].中国园林,2011(7):92-96.
[13]宋小冬,钮心毅.再论居民出行可达性的计算机辅助评价[J].城市规划汇刊,2000(3):18-22,75-79.
[14]Kwan M-P, Murray A T, O’Kelly M E.et al. Recent Advances in Accessibility Research:Representation, Methodology and Applications[J].Journal of Geographical Systems, 2003(5):129-138.
[15]程昌秀,张文尝,陈洁,等.基于空间句法的地铁可达性评价分析—以2008年北京地铁规划图为例[J].地球信息科学,2007(6):31-35.
[16]丁亮,钮心毅,宋小冬.基于移动定位大数据的城市空间研究进展[J].国际城市规划,2015(4):53-58.
[17]曹阳,甄峰.居民住区活动特征识别及影响因素研究[J].规划师,2017(2):124-130.
[18]秦萧,甄峰,熊丽芳,等.大数据时代城市时空间行为研究方法[J].地理科学进展,2013(9):1 352-1 361.
(1)交通运行指数(又称“交通拥堵指数”,Traffic Performance Index,简称“TPI”),即用量化方法表达道路交通运行拥堵程度,是道路交通状态的数字化表达。苏州的交通运行指数大数据几乎覆盖了苏州市区内所有道路,交通指数用介于0~100的数值表达,数值越大表明道路交通越拥堵,数值越小表明交通越畅通。
(2)最大波动幅度指高峰期最长可达性时间与非高峰期最短可达性时间的比值。
(3)“微循环公交”是随着城市与交通规划的不断发展,越来越多的城市区域或社区难以被公共交通有效覆盖,居民居住点或活动区域远离公交、地铁等公共交通站点,由此应运而生的一种乘客“最后一公里”的公共交通解决方案。