Simulation of land use changes using cellular automata and artificial neural network
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.
|Date of creation:||Feb 2012|
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- Christophe Sohn & Bernard Reitel & Olivier Walther, 2009.
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- 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).
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- 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.
- 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 of Agricultural Economists, International Association of Agricultural Economists, vol. 27(3), November.
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