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Research on the Analysis of Campus’ Accessibility Based on Individual Activity Type

  • Baohong HeEmail author
  • Xiang Zhang
  • Xuefeng Li
Conference paper
  • 18 Downloads
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 617)

Abstract

The previous accessibility model is fundamental but neglects activity type on transportation analysis and planning. It fails to comprehensively evaluate individuals’ travel behaviors and their utilizable spatial-temporal resources under different activity types. This paper applies time geography method and classifies the activity types according to the characteristics and the elastic degree of individual activities. And then, the spatial temporal accessibility model and extended model based on the characteristics of different activity types are constructed. Moreover, a case study of campus trip data is given to verify the rationality of the models. The results show that when considering the type of activities, the accessibility does not follow the characteristics of scatter diagram and a “core to periphery” layer structure which is from high to low. Instead, it is determined by the type of activity. The stronger the mandatory activities are, the higher the accessibility of the region will be. Furthermore, when there are only one kind of facilities, the travel distance and time are major factors affecting the value of accessibility, and the personal selection of facilities follows the principle of proximity. The results are more consistent with the real life, therefore the proposed models are more rational. The results of this study provides great reference to the quantification of urban accessibility and theoretical support to the allocation of public urban facilities.

Keywords

Spatio-temporal accessibility Model measuring Activity type Spatio-temporal constraints Personal preference 

Notes

Acknowledgements

Supported by the National Natural Science Foundation of China (51668029).

References

  1. 1.
    Lizhang QHC (2010) Study of temporal and spatial characteristics of students behavior in Hangzhou Xiasha higher education eastern park. Geogr Res 29(7):1281–1290Google Scholar
  2. 2.
    Chen Z (2014) From production space to living space: change of urban function and corresponding spatial planning strategy. City Plan Rev 38(4):28–33Google Scholar
  3. 3.
    Shi LGW (2014) Analysis on the traffic optimization strategies of large-scale campus: a case study of Chenggong Campus, Kunming University of Science and Technology. Huazhong Archit 9:131–135Google Scholar
  4. 4.
    Odoki JB, Kerali HR, Santorini F (2001) An integrated model for quantifying accessibility-benefits in developing countries. Transp Res Part A 35(7):601–623Google Scholar
  5. 5.
    Ben-Akiva ME, Lerman SR (1979) Disaggregate travel and mobility choice models and measures of accessibilityGoogle Scholar
  6. 6.
    Wang Y, Monzon A, Ciommo FD (2014) Assessing the accessibility impact of transport policy by a land-use and transport interaction model—the case of Madrid. Comput Environ Urban Syst 49:126–135Google Scholar
  7. 7.
    Miller H (2007) Place-based versus people-based geographic information science. Geogr Compass 10(3):503–5351749MathSciNetCrossRefGoogle Scholar
  8. 8.
    Kim HM, Kwan MP (2003) Space-time accessibility measures: a geocomputational algorithm with a focus on the feasible opportunity set and possible activity duration. J Geogr Syst 5(1):71–91CrossRefGoogle Scholar
  9. 9.
    Neutens T, Delafontaine M, Schwanen T et al (2011) The relationship between opening hours and accessibility of public service delivery. J Transp Geogr 25(3):128–140Google Scholar
  10. 10.
    Neutens T, Delafontaine M, Scott DM et al (2012) A GIS-based method to identify spatiotemporal gaps in public service delivery. Appl Geogr 32(2):253–264CrossRefGoogle Scholar
  11. 11.
    Neutens T, Schwanen T, Witlox F et al (2009) Equity of urban service delivery: a comparison of different accessibility measures. In: Proceedings of the nectar cluster 6 meeting on accessibility, policy making, spatial planningGoogle Scholar
  12. 12.
    Hansen WG (1959) How accessibility shapes land use. J Am Planning Assoc 25(2):73–76Google Scholar
  13. 13.
    Ingram DR (1971) The concept of accessibility: a search for an operational form. Reg Stud 5(2):101–107CrossRefGoogle Scholar
  14. 14.
    Baxter RS, Lenzi G (1975) The measurement of relative accessibility. Reg Stud 9(1):15–26CrossRefGoogle Scholar
  15. 15.
    Kirby HR (1976) Accessibility indices for abstract road networks. Reg Stud 10(10):479–482CrossRefGoogle Scholar
  16. 16.
    Church R, Revelle C (1974) The maximal covering location problem. Pap Reg Sci 32(1):101–118CrossRefGoogle Scholar
  17. 17.
    Shonick W (1976) Elements of planning for area-wide personal health services. MosbyGoogle Scholar
  18. 18.
    Joseph AE, Bantock PR (1987) Measuring potential physical accessibility to general practitioners in rural areas: a method and case study. Williams & Wilkins and Associates PtyGoogle Scholar
  19. 19.
    Suárez-Vega R, Santos-Peñate DR, Dorta-González P et al (2011) A multi-criteria GIS based procedure to solve a network competitive location problem. Appl Geogr 31(1):282–291Google Scholar
  20. 20.
    Geertman SCM, Eck JRRV (1995) GIS and models of accessibility potential: an application in planning. Int J Geogr Inf Sci 9(1):67–80CrossRefGoogle Scholar
  21. 21.
    Sakkas N, PéREZ J (2006) Elaborating metrics for the accessibility of buildings. Comput Environ Urban Syst 30(5):661–685CrossRefGoogle Scholar
  22. 22.
    Peeters D, Thomas I (2000) Distance predicting functions and applied location-allocation models. J Geogr Syst 2(2):167–184CrossRefGoogle Scholar
  23. 23.
    Wilson AG, Wilson AG (1971) A family of spatial interaction models, and associated developments. Environ Plan A 3(1):1–32CrossRefGoogle Scholar
  24. 24.
    Wilson AG (1967) A statistical theory of spatial distribution models. Transp Res 1(3):253–269CrossRefGoogle Scholar
  25. 25.
    Spiekermann K, Wegener M (1996) Trans-European networks and unequal accessibility in Europe. 4:35–42Google Scholar
  26. 26.
    Vickerman R, Spiekermann K, Wegener M (1999) Accessibility and economic development in Europe. Reg Stud 33(1):1–15CrossRefGoogle Scholar
  27. 27.
    Langford M, Higgs G, Radcliffe J et al (2008) Urban population distribution models and service accessibility estimation. Comput Environ Urban Syst 32(1):66–80CrossRefGoogle Scholar
  28. 28.
    HäGERSTRAND T (1970) What about people in regional science? Pap Reg Sci 24(1):6–21CrossRefGoogle Scholar
  29. 29.
    Lenntorp B (1976) Paths in space-time environments: a time-geographic study of movement possibilities of individuals. Lund Stud Geogr 44Google Scholar
  30. 30.
    Miller HJ (1998) Measuring space-time accessibility benefits within transportation networks: basic theory and computational procedures. Geogr Anal 31(1):1–26MathSciNetCrossRefGoogle Scholar
  31. 31.
    Hsu CI, Hsieh YP (2004) Travel and activity choices based on an individual accessibility model. Pap Reg Sci 83(2):387–406CrossRefGoogle Scholar
  32. 32.
    Chen X, Kwan MP (2012) Choice set formation with multiple flexible activities under space-time constraints. Int J Geogr Inf Sci 26(5):1–21CrossRefGoogle Scholar
  33. 33.
    Cascetta E, Cartenì A, Montanino M (2016) A behavioral model of accessibility based on the number of available opportunities. J Transp Geogr 51:45–58Google Scholar
  34. 34.
    Ren F, Tong D, Kwan MP (2014) Space-time measures of demand for service: bridging location modelling and accessibility studies through a time-geographic framework. Geogr Ann Ser B Hum Geogr 96(4):329–344CrossRefGoogle Scholar
  35. 35.
    Sun Y, Lv B, Zhao Y (2015) A study of county public service facilities distribution assessment based on behavior investigation and GIS: a case study of medical facilities in Dexing. Hum Geogr 3:103–10Google Scholar
  36. 36.
    Hu J, Li G, Zhong G-P (2014) Measuring space-time accessibility within bus network based on space-time process of bus. J Transp Syst Eng Inf Technol 14(4):146–153Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Faculty of Transportation EngineeringKunming University of Science and TechnologyKunmingChina
  2. 2.School of TransportationSoutheast UniversityNanjingChina

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