FUNRESO

FUNctional-structural plant models for improved estimation of crop and soil status based on REmote Sensing Observations

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 Obiettivo del progetto (Objective)

'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.'

Introduzione (Teaser)

The introduction of remote sensing approaches in agriculture is expected to lead to improved monitoring and increased crop production. A European effort developed novel simulation models for estimating crop and soil status remotely.

Descrizione progetto (Article)

Current agriculture practices demand the implementation of modern technological approaches that allow accurate remote monitoring of crop and soil status. So far, the large number of agronomic and environmental variables that could be estimated from remote sensing as well as the accuracy of estimation constituted limiting factors for precision agriculture and environmental assessments and forecasting.

Seeking to address this issue, the EU-funded Funreso project aimed to develop a novel remote sensing approach for improving the accuracy of estimation of crop and soil variables. To this end, the project developed a functional structural plant model (FSPM) capable of taking into account particular water and nitrogen stress responses at the canopy level.

Accuracy improvements in remote sensing information retrieval were achieved by including prior knowledge of vegetation properties and through improved simulation models of canopy reflectance. Such detailed three-dimensional (3D) canopy models were used to retrieve the canopy biophysical and biochemical properties. Remote sensing information was fed into dynamic crop functioning to estimate crop and soil agronomic and environmental variables which are unattainable by direct estimation from remote sensing.

Funreso-developed tools will help remote sensing of crop and soil status and hopefully lead to improved planning and management of agricultural activities.