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Intelligent decision support system based geo-information technology and spatial planning for sustainable water management in Flanders, Belgium
Saleh, H.A.; Allaert, G.; De Sutter, R.; Kellens, W.; De Maeyer, P.; Vanneuville, W. (2008). Intelligent decision support system based geo-information technology and spatial planning for sustainable water management in Flanders, Belgium, in: Feyen, J. et al. (Ed.) (2009). Proceedings of The International Urban Water Conference, Heverlee, Belgium, 15-19 September, 2008: Water and Urban Development Paradigms Towards an Integration of Engineering, Design and Management Approaches. pp. 283-288
In: Feyen, J. et al. (Ed.) (2009). Proceedings of The International Urban Water Conference, Heverlee, Belgium, 15-19 September, 2008: Water and Urban Development Paradigms Towards an Integration of Engineering, Design and Management Approaches. Taylor & Francis: London. ISBN 978-0-415-48334-6, meer

Beschikbaar in  Auteurs 
Documenttype: Congresbijdrage

Trefwoorden
    Artificial intelligence
    Distribution > Geographical distribution
    Hazards > Weather hazards > Floods
    Management
    Planning
    België, Vlaanderen [Marine Regions]

Auteurs  Top 
  • Saleh, H.A.
  • Allaert, G., meer
  • De Sutter, R., meer
  • Kellens, W., meer
  • De Maeyer, P., meer
  • Vanneuville, W., meer

Abstract
    The paper outlines the main features of an intelligent decision support system based on existing and planned tools for optimising water management and flood risk reduction. Up to now, flood risk is increasing and environmental degradation is continuing; this requires developing robotic algorithms that can provide a degree of functionality for spatial representation and flexibility suitable for creating real-time solutions that maximize the urban flood protection measures. Moreover, the volume of data collected is growing rapidly and sophisticated means to efficiently optimise the data are essential. There is a need to develop a shared information system for flood management which will promote model and systems integration, monitoring, and decision making in strategic planning and emergency situations. This advanced area of research is a promising direction for producing an effective time-efficient solution to flood risk reduction where other methods failed. Therefore, the objective of this paper is to bring together innovative methods in the field of artificial intelligence, geo-information technology and spatial and environmental planning to achieve more effective water management and flood risk reduction in Flanders.

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