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Implementation of Multi-scale Agricultural Indicators Exploiting Sentinels (IMAGINES)
Start date: Nov 1, 2012, End date: Jun 30, 2016 PROJECT  FINISHED 

The Copernicus Land Service is being built in the framework of the FP7 geoland2 project, which is setting-up pre-operational infrastructures. IMAGINES intends to ensure the consolidation and the continuity of the R&D efforts initiated in geoland2 to support the operations of the Copernicus Global Land Service, preparing the exploitation of the future Sentinel data in the Copernicus Operations phase beyond 2014. Furthermore, IMAGINES will favor the emergence of new downstream activities dedicated to the monitoring of crop and fodder production. The main objectives of IMAGINES are to (i) investigate the retrieval of multi-sensor and multi-scale biophysical variables (LAI, FAPAR, FCover, Albedo) in view to exploit Sentinel sensors data; (ii) develop qualified softwares able to process multi-sensor data at the global scale on a fully automatic and reliable basis; (iii) complement and contribute to the existing or future agricultural services by providing new data streams relying upon an original method to assess the vegetation above-ground biomass based on the assimilation of above-mentioned satellite products, using either regional or global Land Data Assimilation System infrastructures, in order to monitor the crop/fodder production together with the carbon and water fluxes; (v) demonstrate the added value of this contribution for a community of users acting at global, European, national, and regional scales. The added value of IMAGINES is to build a framework to perform the research and development activities needed for the evolution of the operational Global Land Service, in response to user needs and to new sensors, and to cover the whole chain of value from EO data to the final agricultural indicators directly readable by the end-users.The duration of the project is 40 months, starting in Autumn 2012, with 2 main phases for the definition, and development of demonstration products: first, using PROBA-V 333m data, as proxy of Sentinel-3, to generate hectometric products; then, using using PROBA-V & Landsat-8 (as proxy of Sentinel-3 & Sentinel-2) and Sentinel-1 data to generate multi-sensor decametric products.

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