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A General-Purpose Geosimulation Infrastructure for Spatial Decision Support

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Transactions on Computational Science VI

Part of the book series: Lecture Notes in Computer Science ((TCOMPUTATSCIE,volume 5730))

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.

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Authors and Affiliations

  1. Laboratory of Analysis and Models for Planning (LAMP) Department of Architecture and Planning, University of Sassari, Palazzo Pou Salit, Piazza Duomo 6, 07041, Alghero, Italy

    Ivan Blecic, Arnaldo Cecchini & Giuseppe A. Trunfio

Authors
  1. Ivan Blecic
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  2. Arnaldo Cecchini
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  3. Giuseppe A. Trunfio
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Calgary, 2500 University Drive N.W, T2N 1N4, Calgary, AB, Canada

    Marina L. Gavrilova

  2. OptimaNumerics Ltd., Cathedral House, 23-31 Waring Street, BT1 2DX, Belfast, UK

    C. J. Kenneth Tan

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Blecic, I., Cecchini, A., Trunfio, G.A. (2009). A General-Purpose Geosimulation Infrastructure for Spatial Decision Support. In: Gavrilova, M.L., Tan, C.J.K. (eds) Transactions on Computational Science VI. Lecture Notes in Computer Science, vol 5730. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10649-1_12

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  • DOI: https://doi.org/10.1007/978-3-642-10649-1_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10648-4

  • Online ISBN: 978-3-642-10649-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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