Developing urban land use microsimulation models: an application to Hamilton, Ontario

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In recent years, there has been an increasing interest in developing and using large-scale integrated Transport and Land use Models (ITLUMs) to support the planning process in cities. Such models are complex simulation tools normally used to evaluate the long-term repercussions of proposed urban land-use and/or transport projects. To enhance the predictive ability of these models, recent thinking calls for adopting a micro approach that identifies individual persons, households, firms and developers as the units of analysis. The consensus seems to be that such an approach will lead to disaggregated (also known as microsimulation) models that are behaviorally sound and policy sensitive, capable of promoting sustainable practices in urban areas. In response to this paradigm, the proposed research will seek to develop an operational urban land use microsimulation model. The proposed development environment will be based on components from the "ArcGIS" Geographic Information System, which provides state-of-the-art development tools for maintaining and managing large spatial databases. The unified modeling language (UML) will facilitate the development of object-oriented geodatabase data models as part of the microsimulation models. The first stage of development will involve the creation of synthetic populations of households and business establishments for the study area. The second stage entails the design and development of an integrated framework that encompasses population demographic, firm demographic, land supply and land market modules. The first two modules will microsimulate changes in household structure, residential mobility, and with respect to firms, changes occurring in the spatial distribution of firms and jobs because of failure, establishment, growth/decline and relocation of firms in the city. The third module will simulate the land development process by type of land use, while the fourth will bring together supply and demand for land to simulate the land market. The novelty of the proposed research is the attempt to develop an operational and truly agent-based land use model that is comprehensive, robust, policy sensitive, easily expandable and transferable to other cities.