Coupling canopy functioning and radiative transfer models for remote sensing data assimilation

Crop functioning models (CFM) are used in many agricultural and environment al applications. Remote sensing data assimilation appears as a good tool to provide more information about, canopy state variables in time and space. It permits a reduction in the uncertainties in crop functioning model predi ctions. This study presents the first step of the assimilation of optical r emote sensing data into a crop functioning model. It consists in defining a coupling strategy between well known and validated crop functioning and ra diative transfer models (RTM), applied to wheat crops. The radiative transf er model is first adapted to consistently describe wheat, considering of fo ur layers in the canopy that contain different vegetation organs (soil. yel low leaves and senescent stems, green leaves and stems, green and senescent ears). The coupling is then performed through several state variables: lea f area index, leaf chlorophyll content, organ dry matter and relative water content. The relationships between the CFM outputs (agronomic variables) a nd RTM inputs (biophysical variables) are defined using experimental data s ets corresponding to wheat crops under different climatic and stress condit ions. The coupling scheme is then tested on the data set provided by the Al pilles-ReSeDA campaign. Results show a good fitting between the simulated r eflectance data at top of canopy and the measured ones provided by SPOT ima ges corrected from atmospheric and geometric effects, with a root mean squa re error lower than 0.05 for all the wavebands. (C) 2001 Elsevier Science B .V. All rights reserved.