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Simulation of land use changes using cellular automata and artificial neural network

Author

Listed:
  • OMRANI Hichem
  • CHARIF Omar
  • GERBER Philippe
  • BÓDIS Katalin
  • BASSE Reine Maria

Abstract

This paper presents a method integrating artificial neural network (ANN) in cellular automata (CA) to simulate land use changes in Luxembourg and the areas adjacent to its borders. The ANN is used as a base of CA model transition rule. The proposed method shows promising results for prediction of land use over time. The ANN is validated using cross-validation technique and Receiver Operating Characteristic (ROC) curve analysis, and compared with logit model and a support vector machine approach. The application described in this paper highlights the interest of integrating ANNs in CA based model for land use dynamic simulation.

Suggested Citation

  • OMRANI Hichem & CHARIF Omar & GERBER Philippe & BÓDIS Katalin & BASSE Reine Maria, 2012. "Simulation of land use changes using cellular automata and artificial neural network," LISER Working Paper Series 2012-01, Luxembourg Institute of Socio-Economic Research (LISER).
    • Handle: RePEc:irs:cepswp:2012-01
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    References listed on IDEAS

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    1. R White & G Engelen, 1993. "Cellular Automata and Fractal Urban Form: A Cellular Modelling Approach to the Evolution of Urban Land-Use Patterns," Environment and Planning A, , vol. 25(8), pages 1175-1199, August.
    2. REITEL Bernard & SOHN Christophe & WALTHER Olivier, 2009. "Cross-border metropolitan integration in Europe (Luxembourg, Basel and Geneva)," IRISS Working Paper Series 2009-02, IRISS at CEPS/INSTEAD.
    3. Lin, Huiyan & Lu, Kang Shou & Espey, Molly & Allen, Jeffery, 2005. "Modeling Urban Sprawl and Land Use Change in a Coastal Area-- A Neural Network Approach," 2005 Annual meeting, July 24-27, Providence, RI 19364, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. OMRANI Hichem & CHARIF Omar & KLEIN Olivier & GERBER Philippe, 2010. "An Approach for spatial and temporal data analysis: application for mobility modeling of workers in Luxembourg and its bordering areas," LISER Working Paper Series 2010-16, Luxembourg Institute of Socio-Economic Research (LISER).
    5. Muller, Daniel & Zeller, Manfred, 2002. "Land use dynamics in the central highlands of Vietnam: a spatial model combining village survey data with satellite imagery interpretation," Agricultural Economics, Blackwell, vol. 27(3), pages 333-354, November.
    6. Christophe Sohn & Bernard Reitel & Olivier Walther, 2009. "Cross-Border Metropolitan Integration in Europe: The Case of Luxembourg, Basel, and Geneva," Environment and Planning C, , vol. 27(5), pages 922-939, October.
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    Cited by:

    1. Pere Serra & Luca Salvati, 2022. "Land Change Science and the STEPLand Framework: An Assessment of Its Progress," Land, MDPI, vol. 11(7), pages 1-38, July.
    2. Hashem Dadashpoor & Fardis Salarian, 2020. "Urban sprawl on natural lands: analyzing and predicting the trend of land use changes and sprawl in Mazandaran city region, Iran," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(2), pages 593-614, February.

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    Keywords

    Artificial neural network; Cellular automata; Modelling; Land use changes; Spatial planning and dynamics;
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