Improving Forecasts of Land Use with regionalized maps in the SLEUTH model




land use and cover change, computational simulation, regionalized simulation, historical and sociological characteristics, SLEUTH model


The expansion of cities has significant impacts on economy, ecology, and quality of life, among other sectors. This process affects a large fraction of the world’s population and draws attention of administrators, investors, and scientists. Simulation is an important tool to understand and administer the growth process; however, cities are complex systems, and computer models capture only a fraction of their dynamics. Precision is compromised by simplifications as data averages, and the difficulty to represent human aspects decisive in the evolution of cities. This study tries to mitigate these issues by integrating qualitative information in forecasts computed with the model SLEUTH. Simulations were regionalised using a socioeconomic and historical perspective, which can be explored with other tools. The method was compared to the traditional approach, and the results confirmed a better match between the simulation and the city characteristics.

Author Biographies

Ellen Cristina Wolf Roth, Universidade Tecnológica Federal do Paraná (UTFPR)

PPGCC, Pós-Graduação em Ciência da Computação.

André Koscianski, Universidade Tecnológica Federal do Paraná (UTFPR)

PPGCC, Pós-Graduação em Ciência da Computação.


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How to Cite

Roth, E. C. W., & Koscianski, A. (2020). Improving Forecasts of Land Use with regionalized maps in the SLEUTH model. GeoFocus. International Review of Geographical Information Science and Technology, (25), 153–174.