Developing an Agent-Based Model to Simulate Urban Land-Use Expansion (Case Study: Qazvin)

Extended abstract1-IntroductionUrban land-use expansion is a challenging issue in developing countries. Increases in population as well as the immigration from the villages to the cities are the two major factors for that phenomenon. Those factors have reduced the influence of efforts that try to limit the cities’ boundaries. Thus, spatial planners always look for the models that simulate the expansion of urban land-uses and enable them to prevent unbalanced expansions of cities and guide the developments to the desired areas. Several models have been developed and evaluated for simulating urban land-use expansions. Despite the variety of the models, most of them have focused on simulating urban land-use expansions just around a city. Thus, the regional models that consider wider area are of primary importance.2- Theoretical basesIn this study a new agent-based model has been developed and implemented to simulate urban land-use expansion in Qazvin and Alborz regions of Qazvin state which have an area of 1620 square kilometers. In this model, land-use developers have been treated as agents that move in the landscape explicitly and assess the state of parcels for development. So, the environment of the model is raster. The agents are developed into five groups which have different aims. The agents may fall in competition to develop the same parcels. Moreover, due to the spatial essence of the problem, GIS were used to prepare the environment of agents’ movement and search and to aggregate and analyze the results.Two main steps can be recognized in this model: the Searching step and the Development step:Searching step: The agents are created and distributed in the districts. The selection of districts is probabilistic and is based on the primary probability of selection, assumed for districts. When agents go to the districts, at first they move randomly to the neighborhood of pre-developed areas. Wherever the agent starts its activities, it assesses and saves the state of its current parcel and also its eight adjacent parcels. Next, the agent moves to its best neighbor parcel, or if more than one parcel achieves the same score, it chooses one of them randomly. If the agent movement is finished or it is not able to move to a neighbor parcel, the agent changes the search region in the district and jumps to another position in the same district. Moreover, the agents can search a specific number of districts in the same way. Thus, at the end of each Searching step, each agent records the situation of several visited parcels and sorts them in descending order.De