Understanding Place and Agreeing Purpose: the Role of Virtual Worlds

  • Ian D Bishop
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)


Place is a complex concept. We might limit our thinking to a pair of geographic coordinates or we may seek to understand how a place came to be, what processes are happing in it now, or what options exist for its future. To really know a place we should be aware of all these aspects. Some people, based on prior training or life experience, have an ability to ‘read’ places and immediately understand the geological forces, erosion processes, ecological succession, human activities and climatic constraints which together define character and provide opportunities. Others are not so blessed, and yet agreement on purpose depends upon this prior understanding. Therefore, to reach consensus on land management and policy drivers, we require tools which help all stakeholders to understand what makes a place the way it is and what changes are sustainable. This paper presents recent and ongoing work in environmental visualisation and other tools, such as agent-based modelling, and reviews their demonstrated and potential contribution to understanding and agreement. In particular, work which automates the creation of landscape models, links these to environmental-process simulators for scenario testing, and makes these available as collaborative virtual places is illustrated.


Virtual Environment Virtual World Landscape Model Spatial Data Infrastructure Collaborative Virtual Environment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Agnew J (1987) Place and politics. Allen and Unwin, BostonGoogle Scholar
  2. Appleton K, Lovett A (2003) GIS-based visualisation of rural landscapes: defining ‘sufficient’ realism for environmental decision-making. Landscape and Urban Planning 65(3):117–131.CrossRefGoogle Scholar
  3. Bergen RD, Ulricht CA, Fridley JL, Ganter MA (1995) The validity of computergenerated graphic images of forest landscape. Journal of Environmental Psychology 15(2):135–146CrossRefGoogle Scholar
  4. Bishop ID (2001) Predicting movement choices in virtual environments. Landscape and Urban Planning 56(3–4):97–106CrossRefGoogle Scholar
  5. Bishop ID, Leahy PNA (1989) Assessing the visual impact of development proposals: the validity of computer simulations. Landscape Journal 8:92–100Google Scholar
  6. Champion E, Dave B, Bishop I (2003) Interaction, agency and artifacts. digital design: research and practice. In: Proceedings of the 10th International Conference on Computer Aided Architectural Design Futures, Taiwan. Kluwer Academic Publishers, Norwell, Masachusetts, pp 249–258Google Scholar
  7. Chen T, Stock C, Bishop ID, O’Connor A (2006) Prototyping an in-field collaborative environment for landscape decision support by linking GIS with a game engine. Paper presented at Geoinformation, Wuhan, China, 28–29 October 2006Google Scholar
  8. Cresswell T (2004) Place: a short introduction. Blackwell Publishing, MaldenGoogle Scholar
  9. Pettit C, Cartwright WE, Bishop ID, Park G, Ridley A, Kemp O (2007) eFarmer – a web based farm management and catchment planning tool. Paper accepted for International Congress on Modelling and Simulation, 10–13 December 2007, Christchurch, New ZealandGoogle Scholar
  10. Spottiswood L, Bishop ID (2005) An agent-driven virtual environment for the simulation of land use decision making. Paper presented at International Congress on Modelling and Simulation, 12–15 December 2005, Melbourne, AustraliaGoogle Scholar
  11. Stock C, Bishop ID, O’Connor A (in press) SIEVE: collaborative decision-making in an immersive online environment. Cartography and Geographic Information ScienceGoogle Scholar
  12. Tuan YF (1977). Space and place: the perspective of experience. University of Minnesota Press, MinneapolisGoogle Scholar
  13. Vining J, Orland B (1989) the video advantage: a comparison of two environmental representation techniques. Journal of Environmental Management 29:275–283Google Scholar
  14. Weeks A, Beverly C, Christy B, McLean T (2005) Biophysical approach to predict salt and water loads to upland REALM nodes of Victorian catchments. Paper presented at International Congress on Modelling and Simulation. 12–15 December 2005, Melbourne, AustraliaGoogle Scholar
  15. Wyeld TG, Carroll J, Gibbons C, Ledwich B, Leavy B, Hills J, Docherty M (2007) Doing cultural heritage using the Torque Game Engine: supporting indigenous storytelling in a 3D virtual environment. International Journal of Architectural Computing 5:418–435CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Ian D Bishop
    • 1
  1. 1.CRC for Spatial Information and University of MelbourneAustralia

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