F. Baret, R. Vintila, C. Lazar, N. Rochdi, L. Prévot et al., The adam database and its potential to investigate high temporal sampling acquisition at high spatial resolution for the monitoring of agricultural crops, Romanian Agricultural Research, vol.16, pp.69-80, 2001.

N. Brisson, B. Mary, D. Ripoche, M. H. Jeuffroy, F. Ruget et al., Author-produced version of the article published in Springer's, Recent Advances in Algorithmic Differentiation, pp.59-693527

X. Plenet, D. Cellier, P. Machet, J. M. Meynard, J. M. Delecolle et al., STICS : a generic model for the simulation of crops and their water and nitrogen balances. I: theory and parameterization applied to wheat and corn, Agronomie, vol.18, pp.5-6, 1998.
URL : https://hal.archives-ouvertes.fr/hal-00885888

N. Brisson, F. Ruget, P. Gate, J. Lorgeou, B. Nicoullaud et al., STICS: a generic model for simulating crops and their water and nitrogen balances. II. Model validation for wheat and maize, Agronomie, vol.22, issue.1, pp.69-92, 2002.
DOI : 10.1051/agro:2001005

W. Castaings, D. Dartus, L. Dimet, F. X. Saulnier, and G. M. , Sensitivity analysis and parameter estimation for distributed hydrological modeling: potential of variational methods, Hydrology and Earth System Sciences, vol.13, issue.4, pp.503-517, 2009.
DOI : 10.5194/hess-13-503-2009

URL : https://hal.archives-ouvertes.fr/inria-00391873

A. Griewank, Achieving logarithmic growth of temporal and spatial complexity in reverse automatic differentiation, Optimization Methods and Software, vol.1, issue.1, pp.35-54, 1992.
DOI : 10.1080/10556789208805505

A. Griewank and A. Walther, Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation, 105 in Other Titles in Applied Mathematics. SIAM, 2008.
DOI : 10.1137/1.9780898717761

M. Guérif, V. Houì-es, D. Makowski, and C. Lauvernet, Data assimilation and parameter estimation for precision agriculture using the crop model STICS Working with dynamic crop models: evaluating, analyzing, parameterizing and using them, pp.17-391, 2006.

L. Hascoët and V. Pascual, TAPENADE 2.1 user's guide. Rapport technique 300, 2004.

V. Houì-es, B. Mary, M. Guérif, D. Makowski, and E. Justes, Evaluation of the ability of the crop model stics to recommend nitrogen fertilisation rates according to agro-environmental criteria, Agronomie, vol.24, issue.6, pp.339-349, 2004.

M. Ionescu-bujor and D. G. Cacuci, A comparative review of sensitivity and uncertainty analysis of large-scale systems. I: deterministic methods, Nuclear science and engineering, vol.147, issue.3, pp.189-203, 2004.

C. Lauvernet, F. Baret, L. Hascoët, S. Buis, L. Dimet et al., Multitemporal-patch ensemble inversion of coupled surface???atmosphere radiative transfer models for land surface characterization, Remote Sensing of Environment, vol.112, issue.3, pp.851-861, 2008.
DOI : 10.1016/j.rse.2007.06.027

URL : https://hal.archives-ouvertes.fr/inria-00391894

L. Dimet, F. X. Ngodock, H. E. Navon, and I. M. , Sensitivity analysis in variational data assimilation, J. Meteorol. Soc. Japan pp, pp.145-155, 1997.

L. Dimet, F. X. Talagrand, and O. , Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects, Tellus A, vol.109, issue.2, pp.97-110, 1986.
DOI : 10.1111/j.1600-0870.1986.tb00459.x

J. L. Lions, Optimal control of systems governed by partial differential equations, 1968.
DOI : 10.1007/978-3-642-65024-6

A. Olioso, Y. Inoue, S. Ortega-farias, J. Demarty, J. Wigneron et al., Future directions for advanced evapotranspiration modeling: Assimilation of remote sensing data into crop simulation models and SVAT models, Irrigation and Drainage Systems, vol.69, issue.3-4, pp.3-4, 2005.
DOI : 10.1007/s10795-005-8143-z

N. J. Rosenberg, B. L. Blad, and S. B. Verma, Microclimate: the biological environment, 1983.

F. Ruget, N. Brisson, R. Delecolle, and R. Faivre, Sensitivity analysis of a crop simulation model, STICS, in order to choose the main parameters to be estimated, Agronomie, vol.22, issue.2, pp.133-158, 2002.
DOI : 10.1051/agro:2002009

H. Varella, M. Guérif, and S. Buis, Global Sensitivity Analysis (GSA) Measures the Quality of Parameter Estimation. Case of Soil Parameter Estimation with a Crop Model, IGARSS 2008, 2008 IEEE International Geoscience and Remote Sensing Symposium, pp.310-319, 2010.
DOI : 10.1109/IGARSS.2008.4779531

W. Verhoef, Light scattering by leaf layers with application to canopy reflectance modeling: The SAIL model, Remote Sensing of Environment, vol.16, issue.2, pp.125-141, 1984.
DOI : 10.1016/0034-4257(84)90057-9