by Morteza Yaghoubkhani
Increasingly, in urban areas land is too scarce a commodity to allow it to be taken up in unplanned growth. However, any action – or lack of it – to influence land use has significant consequences both for people, businesses, and organizations in the area, and, more generally, for the urban morphology itself. According to the FAO’s definition of land use planning, estimating the socio-economic conditions of human society and the land potential for development, is necessary to select the best land-use options. So “Planning involves anticipation of the need for change as well as reactions to it” (FAO, 1993). Forecasting the effectiveness as well as the indirect consequences of policies are two main focal points of planning studies. Modeling urban land use changes is helpful to understanding urban dynamics and can be used as an important tool for planners, capable of producing insights about the possible consequences of decisions made by them. Land use modeling can provide a dynamic information base that can inform the policy process at the local, national, and transnational levels. Urban planning and urban models have to be discussed jointly. Couclelis has argued that connecting these two spheres could “amplify the positive synergies between the two domains and enhance the ability of spatial planning to prepare for the future” (Couclelis 2005: 1353).
Land use transformation models can therefore generate data of meaningful representations of the region’s characteristics and allow the processing of different data sets. The models contribute to understand the landscape changes and drivers of the dynamics in the development conditions of each study area. It is also helpful to answer where and at which intensity land-take for urbanization occurs and how spatial growth patterns alter over time; how urbanization (e.g. sprawl) affects large areas overruling local and regional decision.
Land use transformation models can therefore generate data of meaningful representations of the region’s characteristics and allow the processing of different data sets. The models contribute to understand the landscape changes and drivers of the dynamics in the development conditions of each study area. It is also helpful to answer where and at which intensity land-take for urbanization occurs and how spatial growth patterns alter over time; how urbanization (e.g. sprawl) affects large areas overruling local and regional decision.
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