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Application of graph-based model for the quantification of transport network in peri-urban interface of Burdwan City, India

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Abstract

A regional transportation system is an assemblage of multiple and diverse point-to-point movements that occur between similarly multiple origins and destinations. Burdwan city, the administrative, economic and educational capital of Barddhaman district of West Bengal in eastern India, is experiencing continuous growth and change for a long time. As a consequence of rapid economic growth and change, there is high mobility of goods and passengers within and outside the city, which leads to high transportation demand. The city’s road network has a radial form; being shaped by five major roads, it radiates out from central business district to outskirts. In this regard, the present study aims to analyse the application of graph theory of the transport network in peri-urban area of Burdwan city. The study area enjoys multi-modal connectivity with other important regions both within the district as well as with other important destinations within the state. Therefore, network analysis being an important analytical tool of transportation analysis as it involves the depiction of the array of nodes and their relationships with arcs seem pertinent for the study. Thus, to measure the transport network in peri-urban Burdwan, we have employed different indices through apt use of Geographic Information System. The results indicate that the road network connectivity is good in most part of the area. However, we would like to suggest that more accessible and efficient connectivity is required for the peri-urban area while taking into consideration the regional transport network of the area, its future growth potential, and significance of its connection to the Burdwan city.

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Notes

  1. According to the UN-HABITAT’s definition, squatter settlements are regions where occupants don't hold formal residency of their property that they possess for covers and are identified with hunching down and casual rental lodging, absence of essential administrations, prohibition of arranging and building guidelines, and areas with exposures to perilous conditions (UN-HABITAT, 2015).

  2. The arrangement and connectivity of a transport network is known as topology.

  3. A community development block (CD Block) is an administratively allocated rural area for development. This encompasses several gram panchayats, a village-level regional administrative body.

  4. Census of India provides detailed and authentic information on demography, economic activity, literacy and education, housing and household amenities, urbanisation, fertility and mortality, scheduled castes and scheduled tribes, language, religion, migration, disability and many other socio-cultural and demographic data of a decade.

  5. Topographic maps are drawn on relatively large scales, also show important features such as relief, vegetation, water bodies, cultivated land, settlements, and transportation networks, etc.

  6. Google Earth is a geo-browser that accesses online satellite and aerial images and other geographical data to represent the Earth as a three-dimensional world.

References

  1. Simon, D. (2008). Urban environments: Issues on the peri-urban fringe. Annual Review of Environment and Resources,33(1), 167–185. https://doi.org/10.1146/annurev.energy.33.021407.093240.

    Article  Google Scholar 

  2. Ramachandran, R. (1992). Urbanization and urban systems in India. New Delhi: OUP Catalogue.

    Google Scholar 

  3. Brook, R., & Dávila, J. (2000). The peri-urban interface: a tale of two cities. Wales: University of Wales at Bangor.

    Google Scholar 

  4. Fazal, S. (2014). Peri urban livelihoods: Opportunities and challenges. New Dehi: Concept Publishing Company Pvt. Limited.

    Google Scholar 

  5. Pradoto, W. (2012). Development patterns and socioeconomic transformation in peri-urban area: case of Yogyakarta, Indonesia (pp. 25–45). Berlin: Univerlagtuberlin.

    Google Scholar 

  6. Ducruet, C., & Lugo, I. (2013). Structure and dynamics of transportation networks: Models, methods and applications. The SAGE Handbook of Transport Studies. https://doi.org/10.4135/9781446247655.n20.

    Article  Google Scholar 

  7. Raza, M., & Aggarwal, Y. (1986). Transport geography of India: Commodity flows and the regional structure of the Indian economy. New Delhi: Concept Publishing Company.

    Google Scholar 

  8. Laha, M. (2019). Centripetal forces of urbanization in Barddhaman Municipality. West Bengal. Transactions,41(1), 33–50.

    Google Scholar 

  9. Arif, M., Chatterjee, S., & Gupta, K. (2019). Driving forces of urban growth of an Indian city: The Burdwan example. Indian Journal of Regional Science,51(1), 52–64.

    Google Scholar 

  10. Lalanne, L. (1863). Essay of a theory of railroad networks, based on the observation of the facts and on the primordial laws which preside over the grouping of populations. Proceedings of the meetings of the Academy of Sciences,57(2), 206–210.

    Google Scholar 

  11. Currie, A. W. (1959). Economics of Canadian transportation. Toronto: University of Toronto Press.

    Google Scholar 

  12. Garrison, W. L. (1960). Connectivity of the interstate highway system. Papers in Regional Science,6(1), 121–137.

    Article  Google Scholar 

  13. Kissling, C. C. (1966). Transportation networks, accessibility and urban function; An empirical and theoretical analysis. Doctoral Thesis, Department of Geography, McGill University, Canada. Retrieved from https://mcgill.ca.

  14. Beckmann, M. J., & Kansky, K. J. (1967). Structure of transportation networks. Relationships between network geometry and regional characteristics. Econometrica,35(3/4), 564. https://doi.org/10.2307/1905669.

    Article  Google Scholar 

  15. Johnson, L. J., Chorley, R. J., & Haggett, P. (1970). Models in geography. Economic Geography,46(3), 540. https://doi.org/10.2307/143391.

    Article  Google Scholar 

  16. Garrison, W. L., & Marble, D. F. (Eds.) (1974). Graph theoretic concepts. In Transportation geography: Comments and readings (pp. 58–80). New York: McGraw Hill.

    Google Scholar 

  17. Gastner, M. T., & Newman, M. E. J. (2006). The spatial structure of networks. The European Physical Journal B,49(2), 247–252. https://doi.org/10.1140/epjb/e2006-00046-8.

    Article  Google Scholar 

  18. Reggiani, A., Bucci, P., & Russo, G. (2010). Accessibility and impedance forms: Empirical applications to the German commuting network. International Regional Science Review,34(2), 230–252. https://doi.org/10.1177/0160017610387296.

    Article  Google Scholar 

  19. Sreelekha, M. G., Krishnamurthy, K., & Anjaneyulu, M. V. L. R. (2016). Assessment of topological pattern of urban road transport system of Calicut City. Transportation Research Procedia,17, 253–262. https://doi.org/10.1016/j.trpro.2016.11.089.

    Article  Google Scholar 

  20. Black, W. R. (2010). An iterative model for generating transportation networks*. Geographical Analysis,3(3), 283–288. https://doi.org/10.1111/j.1538-4632.1971.tb00370.x.

    Article  Google Scholar 

  21. Freiria, S., Ribeiro, B., & Tavares, A. O. (2015). Understanding road network dynamics: Link-based topological patterns. Journal of Transport Geography,46, 55–66.

    Article  Google Scholar 

  22. Rodrigue, J. P., Comtois, C., & Slack, B. (2016). The geography of transport systems. London: Routledge.

    Book  Google Scholar 

  23. Zhao, F., Sun, H., Wu, J., Gao, Z., & Liu, R. (2016). Analysis of road network pattern considering population distribution and central business district. PLoS ONE,11(3), e0151676. https://doi.org/10.1371/journal.pone.0151676.

    Article  Google Scholar 

  24. Lin, J., & Ban, Y. (2013). Complex network topology of transportation systems. Transport Reviews,33(6), 658–685. https://doi.org/10.1080/01441647.2013.848955.

    Article  Google Scholar 

  25. Registrar General of India. (2013). Census of India, 1981, 1991, 2001, 2011. Retrieved from http://www.censusindia.gov.in.

  26. Ministry of Railways, Indian Railways Annual Statistical Statements. Government of India, New Delhi, 2017-18. Retrieved from http://www.indianrailways.gov.in/railwayboard.

  27. Bevis, H. W. (1956). Forecasting zonal traffic volumes. Traffic Quarterly,10(2), 207–222.

    Google Scholar 

  28. McKinnon, A. C. (1989). The growth of road freight in the UK. International Journal of Physical Distribution & Materials Management,19(4), 3–13.

    Article  Google Scholar 

  29. Survey of India. (1974). Barddhaman district, West Bengal, 1:50,000, sheet 73 M/16. First Edition. Government of India.

  30. Survey of India. (1975). Barddhaman district, West Bengal, 1:50,000, sheet 73 M/15. First Edition. Government of India.

  31. Google Earth 9.0. (2017). Grand trunk road 23° 13′ 08.85″ N, 87° 53′ 44.54″ E, elevation 31 M. 3D map, Roads data layer. Retrieved November 24, 2018 from http://www.earth.google.com.

  32. Environmental Systems Research Institute (ESRI). (2017). ArcGIS Release 10.2.1. Redlands, CA.

  33. Muller, P. O., Taaffe, E. J., Gauthier, H. L., & Hurst, M. E. (1975). Geography of transportation. Economic Geography,51(1), 80. https://doi.org/10.2307/142705.

    Article  Google Scholar 

  34. Xie, F., & Levinson, D. (2009). Topological evolution of surface transportation networks. Computers, Environment and Urban Systems,33(3), 211–223. https://doi.org/10.1016/j.compenvurbsys.2008.09.009.

    Article  Google Scholar 

  35. Cliff, A., Haggett, P., & Ord, K. (1979). Graph theory and geography. Applications of Graph Theory,293, 326.

    Google Scholar 

  36. Robinson, H., & Bamford, C. G. (1978). Geography of transport. London: Macdonald & Evans.

    Google Scholar 

  37. Mayer, H. M. (1979). Urban geography and Chicago in retrospect. Annals of the Association of American Geographers,69(1), 114–118. https://doi.org/10.1111/j.1467-8306.1979.tb01237.x.

    Article  Google Scholar 

  38. Saxena, H. M. (2005). Transport geography. Jaipur: Rawat Publications.

    Google Scholar 

  39. Tini, N. H., & Muhammad, Z. S. (2018). Evaluation of road network topological pattern in Abuja Municipality, Nigeria. European International Journal of Science and Technology,7(1), 53–69.

    Google Scholar 

  40. Taylor, Z., Hoyle, B., & Knowles, R. (2001). Modern transport geography. Economic Geography,77(1), 93. https://doi.org/10.2307/3594099.

    Article  Google Scholar 

  41. Shimbel, A. (1953). Structural parameters of communication networks. The Bulletin of Mathematical Biophysics,15(4), 501–507.

    Article  Google Scholar 

  42. Sarkar, D. (2013). Structural analysis of existing road networks of Cooch Behar District, West Bengal, India: A transport geographical appraisal. Ethiopian Journal of Environmental Studies and Management,6(1), 74–81.

    Google Scholar 

  43. Shen, G. (1997). A fractal dimension analysis of urban transportation networks. Geographical and Environmental Modelling,1, 221–236.

    Google Scholar 

  44. Dinda, S., Ghosh, S., & Das Chatterjee, N. (2018). An analysis of transport suitability, modal choice and trip pattern using accessibility and network approach: a study of Jamshedpur city, India. Spatial Information Research,27(2), 169–186. https://doi.org/10.1007/s41324-018-0223-x.

    Article  Google Scholar 

  45. Ford, A., Barr, S., Dawson, R., & James, P. (2015). Transport accessibility analysis using GIS: Assessing sustainable transport in London. ISPRS, International Journal of Geo-Information,4(1), 124–149. https://doi.org/10.3390/ijgi4010124.

    Article  Google Scholar 

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Acknowledgements

This work was supported by University Grants Commission, New Delhi for providing research assistance. The authors are also grateful to the three anonymous peer reviewers for the constructive comments. Lastly but not the least we give our sincere gratitude to my fellow researchers; Soumen Chatterjee, Swasti Vardhan Mishra and Mehebub Sahana who shared their critical insights in shaping this piece of work.

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Arif, M., Gupta, K. Application of graph-based model for the quantification of transport network in peri-urban interface of Burdwan City, India. Spat. Inf. Res. 28, 447–457 (2020). https://doi.org/10.1007/s41324-019-00305-w

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