Resumo

PRINCIPI, Noelia. Modelado de expansión urbana mediante autómatas celulares y redes neuronales artificiales. Rev. Univ. geogr. [online]. 2022, vol.31, n.1, pp.10-12. ISSN 1852-4265.

Uncontrolled urban growth in areas with deficient infrastructure and inadequate and/or overloaded services is currently one of the central issues in territorial studies. According to the United Nations estimates, by 2030, 60% of the world’s population will be living in cities and 95% of this expansion will take place in developing countries. This article presents a model based on the use of cellular automata and an artificial neural network, which allows the simulation of urban expansion based on criteria that would define future spatial configurations. The methodological development is applied to the city of Luján (Buenos Aires, Argentina) and is carried out in Geographic Information Systems from the automation of the procedures for the analysis of land use changes available in the MOLUSCE tool (Methods for Land Use Change Evaluation) in QGIS. The results show that the expansion trend to 2030 is 20%, which is equivalent to the incorporation of 6.72 km2 of urban coverage, if no type of intervention is carried out. The relevance of this type of work lies in the fact that the results provide technical-scientific support for planning and management agencies in relation to spatial decision making.

Palavras-chave : Urban expansion; Artificial neural network; Cellular automata; Geographic Information Systems; City of Luján.

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