Dynamic modeling of urban expansion using cellular automata: the case of Fortaleza-CE

Abstract

Forecasts of the behaviour of changes that occur in land use are indispensable for adequate urban planning, indicating areas more prone to human occupation. Thus, the study aims to predict the urban expansion of the city of Fortaleza, located in northeastern Brazil, using a dynamic model that combines cellular automata with the Markov Chains (CA-Markov). It was developed through three steps: data acquisition and processing; spatialization of data; and, dynamic spatial modelling. The Markovian transition matrix provided the percentage of changes from one class to another to the simulation algorithm. Actual land use input data for the years 2009 and 2017 showed a transition of 26.50% from vegetated to urbanized areas. The validation of the model showed excellent results (fuzzy similarity index greater than 0.8) to perform future simulations (2020 to 2025). According to forecasts, in 2025, of the 297.10 km² of urbanized and vegetated area, 82.43% will be urbanized, and only 17.57% will be vegetated. The simulation model can be fed by changes that happen within the predicted period, included in the simulation as dynamic variables, obtaining a simulation compatible with these changes.

Keywords:
Urbanization; Dynamic modeling; Cellular automata