A methodology for urban and land-use management simulation using spatial self-organization processes

International audienceIn this study, we develop a methodology based on computational intelligence concepts, for decision making tools using simulation of self-organized complex systems. Land-use management is considered here as the output of sustainable development strategies, dealing with the achievement of many objectives, interacting in a complex way, like environmental, economical and social objectives. The methodology presented here can be considered as a conceptual evolution in simulation processes from the simulations based on rule systems over geographical cellular automata toward the simulations involving self-organized agent-based systems over geographical information systems (GIS). Our methodology is based on self-organization patterns detection which emerge from spatial and behavioral systems. According to the complex systems modelling principles, we let the system evolve by itself with only partial control implemented here by an evolutive and selective process based on a tness function over the whole system