高速公路流的距离衰减模式与空间分异特征——基于福建省高速公路收费站数据的实证研究
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摘要
交通流是社会经济空间联系的直观反映,其距离衰减规律对空间秩序的形成与演化意义重大。利用2016年10月份的福建省高速公路收费站数据,以县区为基本单位,识别高速公路流O-D矩阵;在此基础上,利用空模型法模拟省和县区2个尺度上高速公路流的距离衰减规律,并结合空间分析和相关分析法,探讨高速公路流距离衰减规律的空间分异特征与规律。结果显示,(1)高速公路流主要集中在0~200 km与0~200 min区段,较好地契合了公路运输的经济半径与交通流的时空断裂特征;(2)省域层面上,高速公路流随距离的增加有显著的衰减趋势,当采用路网距离、幂律型衰减函数时,距离衰减系数为2.674,显著高于常规所选数值2;(3)不同县区高速公路流的距离衰减速度在空间上呈显著的圈层模式,与高速公路流的空间分布形成较好的耦合关系;(4)距离衰减规律内生于社会经济空间联系格局,不仅影响空间秩序的形成与演化,也会受空间秩序演化的影响,一定条件下,节点的对外社会经济空间联系强度会随节点规模、人口与经济密度的提高以及区位条件的优化形成自我加速的反馈过程,形成循环累积效应。
As the basic law of geography,the law of distance-decay is of great significance to the formation and evolution of spatial order.Using the data of Fujian expressway toll stations in October 2016,an expressway flow origin-destination matrix was identified with county areas as the basic unit.Cumulative proportion curve,spectrum analysis,and null model were used to simulate the distance-decay effect of expressway flow on the provincial and county scales.Then,combining spatial analysis and correlation analysis,the spatial differentiation characteristics and the distance-decay effect of expressway flow were discussed.The results show that:(1) The expressway flow is mainly concentrated in the 0~200 km and 0~200 min sections,which is in line with the economic radius of road transportation and the temporal and spatial fracture characteristics of traffic flow.(2) The expressway flow has a significant decreasing tendency on the provincial scale with the increase of distance.When using the road distance and power-law decay function,the distance decay coefficient is 2.674,which is significantly higher than the conventional value of 2.(3) The distance-decay rates of the expressway flow in different counties show a clear zonal pattern,corresponding well with the spatial distribution of expressway flow.(4) The law of distance-decay not only influences the evolution of spatial order,but also is influenced by the evolution of spatial order,and it is endogenous to the spatial patterns of socioeconomic activities.Under certain conditions,the strength of socioeconomic spatial connections will form a self accelerating feedback process with the increase of node size,population,and economic density,and the optimization of location conditions.
As the basic law of geography,the law of distance-decay is of great significance to the formation and evolution of spatial order.Using the data of Fujian expressway toll stations in October 2016,an expressway flow origin-destination matrix was identified with county areas as the basic unit.Cumulative proportion curve,spectrum analysis,and null model were used to simulate the distance-decay effect of expressway flow on the provincial and county scales.Then,combining spatial analysis and correlation analysis,the spatial differentiation characteristics and the distance-decay effect of expressway flow were discussed.The results show that:(1) The expressway flow is mainly concentrated in the 0~200 km and 0~200 min sections,which is in line with the economic radius of road transportation and the temporal and spatial fracture characteristics of traffic flow.(2) The expressway flow has a significant decreasing tendency on the provincial scale with the increase of distance.When using the road distance and power-law decay function,the distance decay coefficient is 2.674,which is significantly higher than the conventional value of 2.(3) The distance-decay rates of the expressway flow in different counties show a clear zonal pattern,corresponding well with the spatial distribution of expressway flow.(4) The law of distance-decay not only influences the evolution of spatial order,but also is influenced by the evolution of spatial order,and it is endogenous to the spatial patterns of socioeconomic activities.Under certain conditions,the strength of socioeconomic spatial connections will form a self accelerating feedback process with the increase of node size,population,and economic density,and the optimization of location conditions.
引文
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Liu Y,Kang C,Gao S,et al.2012.Understanding intra-urban trip patterns from taxi trajectory data[J].Journal of Geographical Systems,14(4):463-483.
Liu Y,Wang F,Kang C,et al.2014.Analyzing relatedness by toponym co-occurrences on web pages[J].Transactions in GIS,18(1):89-107.
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Yu X,Wang F H,Liu Y,et al.2013.Reconstructing gravitational attractions of major cities in China from air passenger flow data,2001-2008:A particle swarm optimization approach[J].The Professional Geographer,65(2):265-282.
陈卓,金凤君.2016.北京市等时间交通圈的范围、形态与结构特征[J].地理科学进展,35(3):389-398.[Chen Z,Jin FJ.2016.Scope,shape,and structural characteristics of traffic circles of equal travel time in Beijing[J].Progress in Geography,35(3):389-398]
戴特奇,金凤君,王姣娥.2005.空间相互作用与城市关联网络演进:以我国20世纪90年代城际铁路客流为例[J].地理科学进展,24(2):80-89.[Dai T Q,Jin F J,Wang J E.2005.Spatial interaction and network structure evolvement of cities in term of China's railway passenger flow in 1990s[J].Progress in Geography,24(2):80-89.]
金凤君.2001.基础设施与人类生存环境之关系研究[J].地理科学进展,20(3):275-284.[Jin F J.2001.Infrastructure and the living environment of human being[J].Progress in Geography,20(3):275-284.]
李山,王铮,钟章奇.2012.旅游空间相互作用的引力模型及其应用[J].地理学报,67(4):526-544.[Li S,Wang Z,Zhong Z Q.2012.Gravity model for tourism spatial interaction:Basic form,parameter estimation,and applications[J].Acta Geographica Sinica,67(4):526-544.]
刘瑜,龚俐,童庆禧.2014.空间交互作用中的距离影响及定量分析[J].北京大学学报:自然科学版,50(3):526-534.[Liu Y,Gong L,Tong Q X.2014.Quantifying the distance effect in spatial interactions[J].Acta Scientiarum Naturalium Universitatis Pekinensis,50(3):526-534.]
沈志云,邓学钧.2012.交通运输工程学[M].北京:人民交通出版社.[Shen Z Y,Deng X J.2012.Transportation engineering[M].Beijing:China:China Communications Press.]
王成金.2009.中国交通流的衰减函数模拟及特征[J].地理科学进展,28(5):690-696.[Wang C J.2009.Function simulation and regularity of distance decay of inter-urban traffic flow in China[J].Progress in Geography,28(5):690-696.]
王静远,李超,熊璋,等.2014.以数据为中心的智慧城市研究综述[J].计算机研究与发展,51(2):239-259.[Wang JY,Li C,Xiong Z,et al.2014.Survey of data-centric smart city[J].Journal of Computer Research and Development,51(2):239-259.]
郑清菁,戴特奇,陶卓霖,等.2014.重力模型参数空间差异研究:以中国城市间铁路客流为例[J].地理科学进展,33(12):1659-1665.[Zheng Q J,Dai T Q,Tao Z L,et al.2014.Spatial heterogeneity of gravity model parameters:A case study of inter-city railway passenger flow in China[J].Progress in Geography,33(12):1659-1665.]
Cliff A D,Martin R L.1974.Evaluating the friction of distance parameter in gravity models[J].Regional Studies,8(3):281-286.
Dai T Q,Jin F J.2008.Spatial interaction and network structure evolvement of cities in terms of China's rail passenger flows[J].Chinese Geographical Science,18(3):206-213.
Daniel A G.2007.Spatial structure and spatial interaction:25years later[J].The Review of Regional Studies,37(1):28-38.
Hawelka B,Sitko I,Beinat E,et al.2014.Geo-located twitter as proxy for global mobility patterns[J].Cartography and Geographic Information Science,41(3):260-271.
Isard W.1960.Methods of regional analysis:An introduction to regional science[M].Cambridge:MA:MIT Press.
Johnston R J.1975.Map pattern and friction of distance parameters:A comment[J].Regional Studies,9(3):281-283.
Johnston R.2003.Order in space:Geography as a discipline in distance[M]//Johnston R,Williams M A.A century of British geography.Oxford,UK:Oxford University Press303-345.
Jurdak R,Zhao K,Liu J,et al.2015.Understanding human mobility from twitter[J].Plo S One,10(7):1-31.
Lin P,Yuan N,Zhang S,et al.2015.A comparative analysis of intra-city human mobility by taxi[J].Physica A,420:134-147.
Liu Y,Kang C,Gao S,et al.2012.Understanding intra-urban trip patterns from taxi trajectory data[J].Journal of Geographical Systems,14(4):463-483.
Liu Y,Wang F,Kang C,et al.2014.Analyzing relatedness by toponym co-occurrences on web pages[J].Transactions in GIS,18(1):89-107.
Ravenstein E G.1889.The laws of migration[J].Journal of the Royal Statistical Society,52(2):241-305.
Taylor P J.1971.Distance transformation and distance decay function[J].Geographical Ananlysis,3(3):221-238.
Ullman E L.1956.The role of transportation and the bases for interaction[M]//William L,Thomas J.Man's role in changing the face of the earth.Chicago,IL:The University of Chicago Press:215-229.
Watson J W.1955.Geography:A discipline in distance[J].Scottish Geographical Magazine,71(1):1-13.
Wilson A G.1967.Statistical theory of spatial trip distribution models[J].Transportation Research,1(3):253-269.
Yu X,Wang F H,Liu Y,et al.2013.Reconstructing gravitational attractions of major cities in China from air passenger flow data,2001-2008:A particle swarm optimization approach[J].The Professional Geographer,65(2):265-282.