Agent-based modeling of urban land-use development, case study: Simulating future scenarios of Qazvin city

Abstract

Urban land-use development is a problematic phenomenon in developing countries. Modeling this phenomenon is of considerable interest to urban planners and city managers. Several methods have been developed to simulate the dynamics of land-use changes. However, the complexity of urban growth is considered a factor that impedes the usefulness of such simulation methods. Among the available methods, those considered “agent-based models” have found popularity in simulating land-use development and urban sprawl modeling. These methods use a dynamic bottom-up approach with the actors in land-use development as their basic components.In this paper, a new agent-based model is introduced. This model is equipped with new methods for modeling the movements of agents and competition among agents. The model is used to simulate urban land-use development in the Qazvin province of Iran, which covers an area of 36×45km. The model is first calibrated with existing data and is then used to predict future land-use development. To test development policies, four scenarios are defined. The first scenario reflects the current pattern of development, which is evaluated using the calibrated model. The second and third scenarios examine different policies, including those that act as “incentive” strategies and those that are “punitive.” The fourth scenario focuses on changes to the demographic population of agents. The results reveal that the current trend in urban growth tends to be dispersed in the study area. However, different policies tend to produce different results: in areas in which an incentive policy is in place, 140 clusters of development were detected, while in areas in which a punitive policy is in place, 180 clusters were detected. The incentive strategy is concluded to be more successful than the punitive strategy in reducing the dispersion of development. Change in the population demography is observed to be more efficient in areas of development than in those of dispersion.