The present proposal aims at developing a novel approach for improving the accuracy of estimation of crop and soil variables from remote sensing, which is today limiting for a number of applications as in precision agriculture. The approach is based on the coupling of a dynamic functional crop model to a 3-D canopy structure model. This will allow to take explicitly into account the 3-D architecture of plants while including the effects of water and nitrogen stress and to assimilate directly the reflectance data into the 4-D (3-D plus time) model. Improvements in remote sensing information retrieval accuracy are expected by a) implicit and explicit inclusion of prior knowledge of vegetation parameters, allowing attenuation of problems due to the ill-posed nature of information retrieval from remote sensing and b) better accuracy of canopy reflectance simulations due to the improved realism of such models as compared to classical turbid medium approaches. The research work will be carried out at one of the leading research groups in the world in this sector, the INRA CSE Unit in Avignon (France), and will take advantage of the existing functional structural 4-D models available at the host institution as well as model inversion procedures and experimental results and databases developed by the CSE team.
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