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Environmental Data Warehouse

Environmental Data Warehouse. Cemagref, UR TSCF, TR MOTIVE. 2011 – projet Miriphyque. Analysis. Work of the team. Data warehouse for the integration of simulation results : comparison of results of different versions of simulation models

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Environmental Data Warehouse

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  1. Environmental Data Warehouse Cemagref, UR TSCF, TR MOTIVE 2011 – projet Miriphyque

  2. Analysis

  3. Work of the team • Data warehouse for the integration of simulation results : • comparison of results of different versions of simulation models • comparison between results of simulation models and real data • …

  4. Data warehouse for the integration of simulation results • Data warehouse for the integration of simulation results : • - comparison of results of different versions of simulation models • - comparison between results of simulation models and real data • Applications : • - compare the results issued from different models for estimation of pesticide contamination in soil/water • - compare the results produced by models for the analysis of policy impacts on the land use and on the economic activities (European project Prima – LISC).

  5. Data warehouse for the integration of simulation results We must consider a generic DW structure to compare simulation results produced by different models 1st version of the generic DW structure

  6. Les entrées de simulation Les sorties de simulation • Type de parcelle (Caractéristiques du sol et des écoulements) • Stratégie de traitement (dose et date d'application) • Scénario climatique • (Pluviométrie horaire, température, ETP, … journalières) • Type de culture • Matière active • Débits (L/H) • Ruissellement • Percolation • Subsurface • Concentrations (Mgr/L) • Ruissellement • Percolation • Subsurface • Autres mesures Simulation Travaux concernant SIE Pesticides Le but du projet est d'analyser le transfert de pesticides dans des parcelles (entreposer les résultats de simulation)

  7. Travaux concernant SIE Pesticides

  8. Theoretical aspects: • Modelling spatial data warehouses with software engineering tools based on UML • New structures for specific DW • Techniques for controlling the data • Define new SOLAP operations to analyze data warehouses • Visualisation of spatial data warehouses • Representation of uncertain data

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