Simulation of land use changes using cellular automata and artificial neural network
AbstractThis 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.
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Bibliographic InfoPaper provided by CEPS/INSTEAD in its series CEPS/INSTEAD Working Paper Series with number 2012-01.
Length: 24 pages
Date of creation: Feb 2012
Date of revision:
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Artificial neural network; Cellular automata; Modelling; Land use changes; Spatial planning and dynamics;
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- Christophe Sohn & Bernard Reitel & Olivier Walther, 2009. "Cross-border metropolitan integration in Europe: the case of Luxembourg, Basel, and Geneva," Environment and Planning C: Government and Policy, Pion Ltd, London, vol. 27(5), pages 922-939, October.
- 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.
- 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," CEPS/INSTEAD Working Paper Series 2010-16, CEPS/INSTEAD.
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