Land Cover projection based on Chain Markov and Cellular Automata: Case study of Pampulha - Brazil

Proceedings of the International Conference on Changing Cities II: Spatial, Design, Landscape & Socio-economic Dimensions, – Ano 2015

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Resumo da publicação

Change models are critical for urban planning practices given their usefulness for generating multiple planning scenarios and evaluating their consequences using a set of metrics or rules. The use of scenarios for projection is not new in the planning activities; however, in many developing countries such as Brazil, this tool is hardly ever used. This paper aims to apply the Change Model technique to project the land cover of Pampulha Regional for 2020 by applying Markov chain and Cellular Automata methodologies. In this article, we present the Pampulha Land Cover maps, the Markovian Probability of Changes maps by categories, the Transition area matrix calculated using Markov Chain and the model validation index. Upon completion of the analysis, we can see that both scenarios have the same trend, in particular, we show that the northwest area of Pampulha will present the greatest changes and will require more attention from the city government of the City of Belo Horizonte. This methodology allows to simulate the future land cover and provide an explanation of the future landscape changes in this part of Brazil. The results are especially important considering a significant role this area plays in the local environmental, urban, architectural and cultural life. The neighborhood has been recognized as an example of modern Brazilian architecture since 1940's, the time when the implementation of urban and architectural Pampulha complex, a unique designs from the architect Oscar Niemeyer occurred. Due to the increased real estate value, the area attracted many investors, which led to a more dynamic landscape conformation. Thus, it's defended that scenario simulation methodologies is a mandatory step in a planning process to be faced by Brazilian municipalities, to make good use of human, environmental and economic resources.

Abstract (english text)

Change models are critical for urban planning practices given their usefulness for generating multiple planning scenarios and evaluating their consequences using a set of metrics or rules. The use of scenarios for projection is not new in the planning activities; however, in many developing countries such as Brazil, this tool is hardly ever used. This paper aims to apply the Change Model technique to project the land cover of Pampulha Regional for 2020 by applying Markov chain and Cellular Automata methodologies. In this article, we present the Pampulha Land Cover maps, the Markovian Probability of Changes maps by categories, the Transition area matrix calculated using Markov Chain and the model validation index. Upon completion of the analysis, we can see that both scenarios have the same trend, in particular, we show that the northwest area of Pampulha will present the greatest changes and will require more attention from the city government of the City of Belo Horizonte. This methodology allows to simulate the future land cover and provide an explanation of the future landscape changes in this part of Brazil. The results are especially important considering a significant role this area plays in the local environmental, urban, architectural and cultural life. The neighborhood has been recognized as an example of modern Brazilian architecture since 1940's, the time when the implementation of urban and architectural Pampulha complex, a unique designs from the architect Oscar Niemeyer occurred. Due to the increased real estate value, the area attracted many investors, which led to a more dynamic landscape conformation. Thus, it's defended that scenario simulation methodologies is a mandatory step in a planning process to be faced by Brazilian municipalities, to make good use of human, environmental and economic resources.

Autores do laboratório

  • Prof. Ana Clara Mourão Moura
    Prof. Ana Clara Mourão Moura
    COORDENADORA
  • Grazielle Anjos Carvalho
    Grazielle Anjos Carvalho
    Ex-aluna de Doutorado