A methodological approach to urban land-use change modeling using infill development pattern—a case study in Tabriz, Iran

In recent years, models of land-use change and urban growth have become important tools for city planners, economists, ecologists, and resource managers. In most models, future land-use changes are forecasted based on past development pattern and expansion to periphery. While today, metropolitan areas employ smart-growth strategies. The main objectives in this study are according to the smart-growth infill. In this approach, transmission of incompatible land uses to the outside of the city boundary, redevelopment, improvement, and renovation of urban old district and worn-out texture and reuse of abandoned land to new urban development are considered. In fact, the objective is the using of the infill development pattern to modeling approach for simulating urban future development using potentials inside the city. This paper presents a Land Transformation Model of urban land-use change based on an artificial neural network and a geographical information system. For developing this approach, future development of Tabriz city based on past development trend and infill development pattern is modeled. The modeling result based on past development pattern shows that the 31.26 % of green spaces and 60.93 % of agricultural land and wasteland will be destroyed and the built area will increase 89.75 % from 2005 to 2021. Development of infill development pattern model can regularize urban expansion in the coming decades. The result of infill development pattern, show that the built area will increase 40.32 percent and agricultural land and wasteland area decrease 32.67 percent until 2021. In fact, redevelopment of urban land uses in infill development pattern until 2021, not only preserve the green spaces and agricultural areas but also improve and rehabilitate old and worn-out textures.