Modelagem “CA - Celulas Automatas” para avaliação do crescimento urbano: o caso do entorno do parque Macambira / Anicuns no município de Goiânia

Abstract

The transformations that occur along the cities tend to intensify due to the need of the municipalities for new areas for their growth. Thus, urban planning has become increasingly complex, and this complexity has increasingly required urban spaces for different needs, such as green areas, institutional areas such as secretariats, schools, etc. In this process of urbanization, there are two factors that can be verified to define new areas: population growth and urban expansion pattern. One of the factors that must be analyzed in this relationship between population growth and urbanization growth is its mismatch, because this difference generates an imbalance. In this mismatch, knowledge of land use and its relationship with urban growth allows managers to better frame urban guidelines for proper urban planning. For a better framing of urban planning, the use of tools that allow the determination of urban growth and the analysis of future scenarios is a trend and the use of CA - Automated Cells proves to be an effective tool in the planning and analysis of its growth. One way to use CA is to predict future events relating the land use and population growth model. In this project it was proposed the use of CA tools combined with information on land use and population growth in order to evaluate the growth of the region surrounding the Macambira Anicuns Urban Environmental Program - PUAMA, proposing a methodology of analysis combined with the use of geoprocessing tools linked to the use of CA, thus enabling a greater integration of information and generating products that help in urban planning. The results achieved were the generation of a map collection indicating the growth of the PUAMA region between 2006 and 2016 and a data model with the scenarios from 2016 to 2021, indicating the places with the greatest impact on the region's growth. And to validate the model, 2018 data were used to verify the reliability of the modeled data and these reached a correlation of 83.73% for the empty lot areas. Given this reality, the simulation model proved to be effective and reliable with reality allowing the manager an analysis tool for the best urban planning.