Objective
Objectives. The aim of the project is to develop new methods of data fusion and to provide Grid-based solutions for image processing and geospatial modelling, targeting to improve applied agricultural problems solving. To acieve this goal several concrete objectives will be followed: - to develop robust method of environmental model adaptation, and verify this approach for Numerical Weather Prediction (NWP) model for the region of Ukraine; - to determine optimal set of variables for data assimilation for NWP model for the region of Ukraine; - to improve existing methods of yield prediction to assimilate data of NWP; - to adopt improved methods of yield prediction for different regions (in particular Ukraine); - to develop problem-oriented environment targeting NWP model. The particular problems that will be solved are adaptation and data assimilation for Weather Research and Forecasting (WRF) model; - to harmonize existing Grid resources of Ukraine with CEOS (Committee on Earth Observing Satellites) Working Group on Information Systems and Services (WGISS) initiative Wide Area Grid (WAG); - to fill the gap in existing Grid infrastructure such as geospatial data archives and visualization. Methodology. For solution of complex optimization problems arising in adaptation of environmental models and data assimilation genetic algorithms will be applied. Class of models for which genetic algorithms approach are appropriate ones will be identified. The improvement of yield prediction models will be done using outputs of NWP model which is adapted to particular region. Archive for geospatial data and visualization services will be developed using Grid technology. Expected results. - new intelligent methods for complex environmental models adaptation will be developed, and verified for NWP model for the region of Ukraine; - data, software and hardware capabilities will be established in order to create initial conditions for regional Weather Research & Forecasting (WRF) NWP model; the optimal set of satellite data for NWP data assimilation will be identified; - existing methods of yield prediction will be improved by assimilating data from NWP models and adaptation of models to particular region; - OGSA-DAI Grid archive for geospatial data will be developed and deployed on Satellite Data Storage System of IKI-RAN; - Grid-enabled visualization service for geospatial data will be developed; - developed services and existing Grid infrastructure will be harmonized with WAG project initiated by CNES and CEOS. The harmonization will be done in the view of metadata representation, data formats exchange, common security policy.
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BRATISLAVA
Slovakia