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Modeling Urban Land Use Change and Urban Sprawl: Calgary, Alberta, Canada

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  • Heng Sun

    ()

  • Wayne Forsythe

    ()

  • Nigel Waters

    ()

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    Abstract

    This paper implements a land use classification for the City of Calgary, Alberta, Canada, using an object-oriented approach for six Landsat TM and ETM+ images and simulates the land use pattern in the future using Markov Chain analysis and Cellular Automata analysis based on the interactions between these land uses and the transportation network. Shannon’s Entropy (an urban sprawl index) based on the land use classification results is used to measure urban sprawl. This research proves that an object-oriented approach can produce satisfactory classification results. It reveals the manner in which land use is likely to develop in the future, and demonstrates that urban sprawl continued to grow in Calgary during the years between 1985 and 2001. Such models are useful for providing the building blocks for traditional four-step transportation planning models. Copyright Springer Science+Business Media, LLC 2007

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    File URL: http://hdl.handle.net/10.1007/s11067-007-9030-y
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    Bibliographic Info

    Article provided by Springer in its journal Networks and Spatial Economics.

    Volume (Year): 7 (2007)
    Issue (Month): 4 (December)
    Pages: 353-376

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    Handle: RePEc:kap:netspa:v:7:y:2007:i:4:p:353-376

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    Web page: http://www.springerlink.com/link.asp?id=106607

    Related research

    Keywords: Urban sprawl; Road networks; Entropy; Object-oriented classification; Cellular automata; Markov chain analysis;

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    1. Raquel Espino & Juan Ortúzar & Concepción Román, 2006. "Confidence Interval for Willingness to Pay Measures in Mode Choice Models," Networks and Spatial Economics, Springer, vol. 6(2), pages 81-96, June.
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