In this paper we present the general-purpose simulation infrastructure MAGI, with features and computational strategies particularly relevant for strongly geo-spatially oriented simulations. Its main characteristics are (1) a comprehensive approach to geosimulation modelling, with a flexible underlying meta-model formally generalising a variety of types of models, both from the cellular automata and from the agent-based family of models, (2) tight interoperability between GIS and the modelling environment, (3) computationally efficiency and (4) user-friendliness. Both raster and vector representation of simulated entities are allowed and managed with efficiency, which is obtained through the integration of a geometry engine implementing a core set of operations on spatial data through robust geometric algorithms, and an efficient spatial indexing strategy for moving agents. We furthermore present three test-case applications to discuss its efficiency, to present a standard operational modelling workflow within the simulation environment and to briefly illustrate its look-and-feel. © 2009 Springer-Verlag Berlin Heidelberg.
A general-purpose geosimulation infrastructure for spatial decision support
BLECIC, IVAN;
2009-01-01
Abstract
In this paper we present the general-purpose simulation infrastructure MAGI, with features and computational strategies particularly relevant for strongly geo-spatially oriented simulations. Its main characteristics are (1) a comprehensive approach to geosimulation modelling, with a flexible underlying meta-model formally generalising a variety of types of models, both from the cellular automata and from the agent-based family of models, (2) tight interoperability between GIS and the modelling environment, (3) computationally efficiency and (4) user-friendliness. Both raster and vector representation of simulated entities are allowed and managed with efficiency, which is obtained through the integration of a geometry engine implementing a core set of operations on spatial data through robust geometric algorithms, and an efficient spatial indexing strategy for moving agents. We furthermore present three test-case applications to discuss its efficiency, to present a standard operational modelling workflow within the simulation environment and to briefly illustrate its look-and-feel. © 2009 Springer-Verlag Berlin Heidelberg.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.