Title: Land use changes modelling using advanced methods: Cellular automata and artificial neural networks. The spatial and explicit representation of land cover dynamics at the cross-border region scale
Authors: BASSE Reine MarieOMRANI HichemCHARIF OmarGERBER PhilippeBODIS Katalin
Citation: APPLIED GEOGRAPHY vol. 53 p. 160-171
Publication Year: 2014
JRC N°: JRC91145
ISSN: 0143-6228
URI: http://www.sciencedirect.com/science/article/pii/S0143622814001325
DOI: 10.1016/j.apgeog.2014.06.016
Type: Articles in periodicals and books
Abstract: Identifying and evaluating the driving forces that are behind land use and land cover changes remains one of the most difficult exercises that geographers and environmental scientists must continually address. The difficulty emerges from the fact that in land use and land cover systems, multiple actions and interactions between different factors (e.g., economic, political, environmental, biophysical, insti- tutional, and cultural) come into play and make it difficult to understand how the processes behind the changes function. Using advanced methods, such as Cellular Automata (CA) and Artificial Neural Net- works (ANNs), the results highlight that these tools are adequate in formalising knowledge regarding land use systems in cross-border regions. Moreover, because modelling land use changes using big data is gaining increasing popularity, ANN techniques could contribute to improving the calibration of cellular automata-based land use models.
JRC Directorate:Energy, Transport and Climate

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