A cellular automata model incorporating land tax for predicting urban growth
This study looks at the possibility of developing a cellular automata model incorporating tax and geographic conditions for simulating urban growth process with a view of using it in the future as a tool for directing growth in the city of Makassar, Indonesia. The developed model uses land tax values in addition to geographic condition constraints such as rivers, flood prone and nature conservation areas. The CA model with incorporated tax constraints is examined together with a model with only the geographical constraints. Their performance is tested using the multi-scale goodness of-fit. The CA model incorporating the land tax constraints produced slightly better simulation results under different parameter settings as compared with the geographic conditions. A calibrated model with an average prediction accuracy of over 75% becomes the basis for predicting the growth of urban areas in the city of Makassar until the year 2025.
Keywords: urban sprawl, land use control, urban growth simulation, cellular automata, land tax, multi scale goodness of-fit, Makassar, Indonesia