This work shows the complexity of urban growthUrban growth and its modelling using Cellular AutomataCellular automata (CA). The importance of understanding urban sustainability for planners and governments is highlighted, especially in cities with more than one million inhabitants. Cellular automataCellular automata are an effective tool to simulate and predict urban transformation, allowing a better understanding of the spatio-temporal dynamics of urban growthUrban growth, in addition to being integrated into geographic information systems (GIS), to facilitate their management. The model operates with deterministic transition rulesDeterministic transition rules, which are evaluated for their ability to represent realistic urban phenomena and their potential to describe urban planning. The limitations and uncertainty inherent in deterministic CA models are highlighted, as well as the need to incorporate additional factors that propose improvements in the methodology and greater integration of CA with other models to advance urban planning and territorial intelligence.

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Territorial Intelligence in City Growth with Cellular Automata

  • E. Jiménez-López,
  • R. E. Lozoya-Ponce,
  • E. Cadena-Vargas

摘要

This work shows the complexity of urban growthUrban growth and its modelling using Cellular AutomataCellular automata (CA). The importance of understanding urban sustainability for planners and governments is highlighted, especially in cities with more than one million inhabitants. Cellular automataCellular automata are an effective tool to simulate and predict urban transformation, allowing a better understanding of the spatio-temporal dynamics of urban growthUrban growth, in addition to being integrated into geographic information systems (GIS), to facilitate their management. The model operates with deterministic transition rulesDeterministic transition rules, which are evaluated for their ability to represent realistic urban phenomena and their potential to describe urban planning. The limitations and uncertainty inherent in deterministic CA models are highlighted, as well as the need to incorporate additional factors that propose improvements in the methodology and greater integration of CA with other models to advance urban planning and territorial intelligence.