全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
PLOS ONE  2012 

Network Structure and City Size

DOI: 10.1371/journal.pone.0029721

Full-Text   Cite this paper   Add to My Lib

Abstract:

Network structure varies across cities. This variation may yield important knowledge about how the internal structure of the city affects its performance. This paper systematically compares a set of surface transportation network structure variables (connectivity, hierarchy, circuity, treeness, entropy, accessibility) across the 50 largest metropolitan areas in the United States. A set of scaling parameters are discovered to show how network size and structure vary with city size. These results suggest that larger cities are physically more inter-connected. Hypotheses are presented as to why this might obtain. This paper then consistently measures and ranks access to jobs across 50 US metropolitan areas. It uses that accessibility measure, along with network structure variables and city size to help explain journey-to-work time and auto mode share in those cities. A 1 percent increase in accessibility reduces average metropolitan commute times by about 90 seconds each way. A 1 percent increase in network connectivity reduces commute time by 0.1 percent. A 1 percent increase in accessibility results in a 0.0575 percent drop in auto mode share, while a 1 percent increase in treeness reduces auto mode share by 0.061 percent. Use of accessibility and network structure measures is important for planning and evaluating the performance of network investments and land use changes.

References

[1]  Glaeser E (2011) Triumph of the City. New York: Penguin Press.
[2]  Derrible S, Kennedy C (2010) The complexity and robustness of metro networks. Physica A: Statistical Mechanics and its Applications 389: 3678–3691.
[3]  Derrible S, Kennedy C (2009) Network analysis of world subway systems using updated graph theory. Transportation Research Record: Journal of the Transportation Research Board 2112: 17–25.
[4]  Derrible S, Kennedy C (2010) Characterizing metro networks: state, form, and structure. Trans- portation 37: 275–297.
[5]  Roth C, Kang S, Batty M, Barthelemy M (2011) Long-time limit of world subway networks. Arxiv preprint arXiv: 11055294.
[6]  Jiang B (2009) Street hierarchies: a minority of streets account for a majority of traffic flow. International Journal of Geographical Information Science 23: 1033–1048.
[7]  Jiang B (2007) A topological pattern of urban street networks: Universality and peculiarity. Physica A: Statistical Mechanics and its Applications 384: 647–655.
[8]  Jiang B, Claramunt C (2004) Topological analysis of urban street networks. Environment and Planning B 31: 151–162.
[9]  Jiang B, Liu C (2009) Street-based topological representations and analyses for predicting traffic ow in gis. International Journal of Geographical Information Science 23: 1119–1137.
[10]  Jiang B, Zhao S, Yin J (2008) Self-organized natural roads for predicting traffic ow: a sensitivity study. Journal of statistical mechanics: Theory and experiment 2008: P07008.
[11]  Samaniego H, Moses M (2008) Cities as organisms: Allometric scaling of urban road networks. Journal of Transport and Land Use 1:
[12]  Lammer S, Gehlsen B, Helbing D (2006) Scaling laws in the spatial structure of urban road net- works. Physica A: Statistical Mechanics and its Applications 363: 89–95.
[13]  Kuehnert C, Helbing D, West G (2006) Scaling laws in urban supply networks. Physica A: Statis- tical Mechanics and its Applications 363: 96–103.
[14]  Helbing D, Kuehnert C, Lammer S, Johansson A, Gehlsen B, et al. (2009) Power laws in urban sup- ply networks, social systems, and dense pedestrian crowds. Complexity Perspectives in Innovation and Social Change 433–450.
[15]  Melo P, Graham D, Noland R (2009) A meta-analysis of estimates of urban agglomeration economies. Regional Science and Urban Economics 39: 332–342.
[16]  Graham D, Dender K (2009) Estimating the agglomeration benefits of transport investments: some tests for stability. Transportation 1–18.
[17]  Graham D, Kim H (2008) An empirical analytical framework for agglomeration economies. The Annals of Regional Science 42: 267–289.
[18]  Graham D (2007) Variable returns to agglomeration and the effect of road traffic congestion. Journal of Urban Economics 62: 103–120.
[19]  Graham D (2007) Agglomeration, productivity and transport investment. Journal of Transport Economics and Policy (JTEP) 41: 317–343.
[20]  Glaeser E, Resseger M (2010) The complementarity between cities and skills*. Journal of Regional Science 50: 221–244.
[21]  Glaeser E, Kerr W (2009) Local industrial conditions and entrepreneurship: How much of the spatial distribution can we explain? Journal of Economics & Management Strategy 18: 623–663.
[22]  Glaeser E (2008) Cities, agglomeration, and spatial equilibrium. Oxford University Press.
[23]  West G (2010) Integrated sustainability and the underlying threat of urbanization. Global Sus- tainability: A Nobel Cause: 9.
[24]  Strogatz S (2009) Math and the city. The New York Times, May 19.
[25]  Bettencourt L, Lobo J, Strumsky D, West G (2010) Urban scaling and its deviations: Revealing the structure of wealth, innovation and crime across cities. PloS one 5: e13541.
[26]  Bettencourt L, West G (2010) A unified theory of urban living. Nature 467: 912–913.
[27]  Bettencourt L, Lobo J, West G (2009) The self similarity of human social organization and dynamics in cities. Complexity Perspectives in Innovation and Social Change 221–236.
[28]  Bettencourt L, Lobo J, Strumsky D (2007) Invention in the city: Increasing returns to patenting as a scaling function of metropolitan size. Research Policy 36: 107–120.
[29]  Arbesman S, Kleinberg J, Strogatz S (2008) Superlinear scaling for innovation in cities. Arxiv preprint arXiv: 08094994.
[30]  Ades A, Glaeser E (1995) Trade and circuses: explaining urban giants. The Quarterly Journal of Economics 110: 195.
[31]  Gordon P, Richardson H, Jun M (1991) The commuting paradox evidence from the top twenty. Journal of the American Planning Association 57: 416–420.
[32]  Gordon P, Kumar A, Richardson H (1988) Beyond the journey to work. Transportation Research Part A: General 22: 419–426.
[33]  Stigler G (1951) The division of labor is limited by the extent of the market. The Journal of Political Economy 59: 185–193.
[34]  Hamilton B, Roell A (1982) Wasteful commuting. The Journal of Political Economy 90: 1035–1053.
[35]  Parthasarathi P, Levinson D (2010) Network structure and metropolitan mobility. Working Papers.
[36]  Levinson D, Huang A (2011) A positive theory of network connectivity. Environment and Planning part B.
[37]  Mogridge M, Holden D, Bird J, Terzis G (1987) The downs/thomson paradox and the transporta- tion planning process. International Journal of Transport Economics 14: 283–311.
[38]  Mogridge M (1990) Travel in towns: jam yesterday, jam today and jam tomorrow? Macmillan London.
[39]  Downs A (1992) Stuck in traffic: Coping with peak-hour traffic congestion. Brookings Institution Press.
[40]  Xie F, Levinson D (2011) Evolving Transportation Networks. Springer.
[41]  Barthelemy M (2010) Spatial networks. Physics Reports.
[42]  Kansky K (1963) Structure of transportation networks: relationships between network geometry and regional characteristics. University of Chicago, Department of Geography.
[43]  Xie F, Levinson D (2007) Measuring the structure of road networks. Geographical Analysis 39: 336–356.
[44]  Haggett P, Chorley R (1969) Network analysis in geography. Edward Arnold.
[45]  Levinson D, El-Geneidy A (2009) The minimum circuity frontier and the journey to work. Regional Science and Urban Economics 39: 732–738.
[46]  El-Geneidy A, Levinson D (2006) Access to destinations: Development of accessibility measures. Minnesota Department of Transportation, Research Services Section.
[47]  Levinson D, Kumar A, Center S (1995) A multi-modal trip distribution model. Transportation Research Record 1466: 124–131.
[48]  Schrank D, Lomax T (2009) The 2009 urban mobility report. College Station: Texas Transporta- tion Institute, Texas A&M University.
[49]  Batty M (2008) The size, scale, and shape of cities. Science 319: 769.
[50]  Bettencourt L, Lobo J, Helbing D, Kuehnert C, West G (2007) Growth, innovation, scaling, and the pace of life in cities. Proceedings of the National Academy of Sciences 104: 7301.
[51]  Employment, hours, and earnings from the current employment statistics survey. URL http://data.bls.gov/cgi-bin/surveymost. Key: CES2011 Annotation: (National) Series Id: CES0000000001 Seasonally Adjusted, Super Sector: Total nonfarm, Industry: Total nonfarm, Data Type: All Employees, Thousands.
[52]  Southworth M, Ben-Joseph E (2003) Streets and the Shaping of Towns and Cities. Island Pr.
[53]  Levinson D, Xie F, Oca N (2007) Forecasting and evaluating network growth. Networks and Spatial Economics 1–24.
[54]  Parthasarathi P, Hochmair H, Levinson D (2010) Network structure and activity spaces. Working Papers.
[55]  Tomer A, Kneebone E, Puentes R, Berube A (2011) Missed opportunity: Transit and jobs in metropolitan america. Technical report, Brookings Institution.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133