Pyroxene: A Territorial Decision Support System Based on Spatial Simulators Integration for Forest Fire Risk Management

Pyroxene: A Territorial Decision Support System Based on Spatial Simulators Integration for Forest Fire Risk Management

Eric Maillé (Cemagref, Mediterranean Ecoystems and Risks Research Group (EMAX), Territorial Management Department (GT), France) and Bernard Espinasse (Aix-Marseilles University, Information Sciences and Systems Laboratory, LSIS UMR CNRS 6168, France)
DOI: 10.4018/978-1-4666-0333-2.ch014
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Abstract

Medium term management of territorial risk increase requires decision support tools able to represent and simulate spatial dynamics. For forest fire risk, simulators of spatial dynamics of both fuel zones and vulnerable zones are produced by specialised disciplines, like ecology and geography. In order to integrate simulators of spatial dynamics of different themes at different scale levels, this paper proposes a spatial agent and GIS based software infrastructure called Pyroxene. This infrastructure is designed to implement “models for models integration”, specified by domain expert users. To do so, end users have to use a specification framework, specifically designed for spatio-dynamic models integration. The purpose of the implemented platform is to execute and synchronise integrated simulations. To operate the semantic and syntax requirements of such integration, the platform is structured in an HLA-like architecture, and implemented as a multi-agents system for models integration, compliant with the FIPA specification. It is also organised around a GIS. First steps of validation confirm the validity of the system at the functional level and precise the limits of using the approach on the operational level.
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2. Multi-Modelling Of Spatial Dynamics Leading To Changes In Forest Fire Risk

Forest fire risk increase stems from the competition between two very different spatial dynamics: fuel spaces dynamics (forest ecosystems), and vulnerable spaces dynamics, in particular discontinuously urbanised territories (Jappiot et al., 2000). Both of them are controlled by the social regulation system, for example through land planning. In Figure 1, we describe the link between land cover dynamics and changes in the map of risk levels, as well as the limits of the integrated system to be modelled.

Figure 1.

Integration of land cover change models to simulate risk evolutions

In order to support spaces management planning decision-making, it is not required to represent the social system of regulation decision making itself. This social system is, in fact, the end user of our specified tool. The end user will elaborate and test different planning scenarios in order to assess their possible effect on the future map of the risk levels during the plan execution period.

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