C. Atzberger, Advances in Remote Sensing of Agriculture: Context Description, Existing Operational Monitoring Systems and Major Information Needs, Remote Sensing, vol.5, issue.2, pp.949-981, 2013.
DOI : 10.3390/rs5020949

B. Grieve, Localized multispectral crop imaging sensors: Engineering & validation of a cost effective plant stress and disease sensor, 2015 IEEE Sensors Applications Symposium (SAS), pp.1-6, 2015.
DOI : 10.1109/SAS.2015.7133588

B. Duchemin, Impact of Sowing Date on Yield and Water Use Efficiency of Wheat Analyzed through Spatial Modeling and FORMOSAT-2 Images, Remote Sensing, vol.7, issue.5, pp.5951-5979, 2015.
DOI : 10.3390/rs70505951

D. J. Mulla, Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps, Biosystems Engineering, vol.114, issue.4, pp.358-371, 2013.
DOI : 10.1016/j.biosystemseng.2012.08.009

J. Betbeder, R. Fieuzal, and F. Baup, Assimilation of LAI and Dry Biomass Data From Optical and SAR Images Into an Agro-Meteorological Model to Estimate Soybean Yield, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.9, issue.6
DOI : 10.1109/JSTARS.2016.2541169

URL : https://hal.archives-ouvertes.fr/hal-01334824

M. Claverie, Maize and sunflower biomass estimation in southwest France using high spatial and temporal resolution remote sensing data, Remote Sensing of Environment, vol.124, pp.844-857, 2012.
DOI : 10.1016/j.rse.2012.04.005

URL : https://hal.archives-ouvertes.fr/ird-00718813

B. Duchemin, A simple algorithm for yield estimates: Evaluation for semi-arid irrigated winter wheat monitored with green leaf area index, Environmental Modelling & Software, vol.23, issue.7, pp.876-892, 2008.
DOI : 10.1016/j.envsoft.2007.10.003

URL : https://hal.archives-ouvertes.fr/ird-00388344

J. Liu, E. Pattey, and G. Jégo, Assessment of vegetation indices for regional crop green LAI estimation from Landsat images over multiple growing seasons, Remote Sensing of Environment, vol.123, pp.347-358, 2012.
DOI : 10.1016/j.rse.2012.04.002

D. Haboudane, Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture, Remote Sensing of Environment, vol.90, issue.3, pp.337-352, 2004.
DOI : 10.1016/j.rse.2003.12.013

H. Skriver, M. T. Svendsen, and A. G. Thomsen, Multitemporal C- and L-band polarimetric signatures of crops, IEEE Transactions on Geoscience and Remote Sensing, vol.37, issue.5, pp.2413-2429, 1999.
DOI : 10.1109/36.789639

F. Mattia, Multitemporal c-band radar measurements on wheat fields, IEEE Transactions on Geoscience and Remote Sensing, vol.41, issue.7, pp.1551-1560, 2003.
DOI : 10.1109/TGRS.2003.813531

H. Mcnairn and B. Brisco, The application of C-band polarimetric SAR for agriculture: a review, Canadian Journal of Remote Sensing, vol.36, issue.3, pp.525-542, 2004.
DOI : 10.5589/m03-069

A. Balenzano, Dense Temporal Series of C- and L-band SAR Data for Soil Moisture Retrieval Over Agricultural Crops, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.4, issue.2, pp.439-450, 2011.
DOI : 10.1109/JSTARS.2010.2052916

M. Aubert, Analysis of TerraSAR-X data sensitivity to bare soil moisture, roughness, composition and soil crust, Remote Sensing of Environment, vol.115, issue.8, pp.1801-1810, 2011.
DOI : 10.1016/j.rse.2011.02.021

URL : https://hal.archives-ouvertes.fr/hal-00602355

F. Wu, Rice Crop Monitoring in South China With RADARSAT-2 Quad-Polarization SAR Data, IEEE Geoscience and Remote Sensing Letters, vol.8, issue.2, pp.196-200, 2011.
DOI : 10.1109/LGRS.2010.2055830

R. Fieuzal, F. Baup, and C. Marais-sicre, Monitoring Wheat and Rapeseed by Using Synchronous Optical and Radar Satellite Data???From Temporal Signatures to Crop Parameters Estimation, Advances in Remote Sensing, vol.02, issue.02, pp.162-180, 2013.
DOI : 10.4236/ars.2013.22020

C. Liu, Multiyear Crop Monitoring Using Polarimetric RADARSAT-2 Data, IEEE Transactions on Geoscience and Remote Sensing, vol.51, issue.4, pp.2227-2240, 2013.
DOI : 10.1109/TGRS.2012.2208649

G. Wiseman, RADARSAT-2 Polarimetric SAR Response to Crop Biomass for Agricultural Production Monitoring, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.7, issue.11, pp.4461-4471, 2014.
DOI : 10.1109/JSTARS.2014.2322311

S. Paloscia, The potential of C- and L-band SAR in estimating vegetation biomass: the ERS-1 and JERS-1 experiments, IEEE Transactions on Geoscience and Remote Sensing, vol.37, issue.4, pp.2107-2110, 1999.
DOI : 10.1109/36.774723

N. Baghdadi, Potential of SAR sensors TerraSAR-X, ASAR/ENVISAT and PALSAR/ALOS for monitoring sugarcane crops on Reunion Island, Remote Sensing of Environment, vol.113, issue.8, pp.1724-1738, 2009.
DOI : 10.1016/j.rse.2009.04.005

G. Fontanelli, Sensitivity analysis of X-band SAR to wheat and barley leaf area index in the Merguellil Basin, Remote Sensing Letters, vol.4, issue.11, pp.1107-1116, 2013.
DOI : 10.5194/hess-15-345-2011

URL : https://hal.archives-ouvertes.fr/hal-00906743

J. M. Lopez-sanchez, I. Hajnsek, and J. D. Ballester-berman, First Demonstration of Agriculture Height Retrieval With PolInSAR Airborne Data, IEEE Geoscience and Remote Sensing Letters, vol.9, issue.2, pp.242-246, 2012.
DOI : 10.1109/LGRS.2011.2165272

. Betbeder, Contribution of multitemporal polarimetric synthetic aperture radar
URL : https://hal.archives-ouvertes.fr/hal-01331288

J. Lee and E. Pottier, Polarimetric Radar Imaging: From Basics to Applications, 2009.
DOI : 10.1201/9781420054989

URL : https://hal.archives-ouvertes.fr/hal-00351911

X. Jiao, The sensitivity of RADARSAT-2 polarimetric SAR data to corn and soybean leaf area index, Canadian Journal of Remote Sensing, vol.37, issue.1, pp.69-81, 2011.
DOI : 10.1080/01431169608949158

Y. Kim, Radar vegetation index for estimating the vegetation water content of rice and soybean, IEEE Geosci. Remote Sens. Lett, vol.9, pp.564-568, 2012.

S. Gao, Estimating the Leaf Area Index, height and biomass of maize using HJ-1 and RADARSAT-2, International Journal of Applied Earth Observation and Geoinformation, vol.24, pp.1-8, 2013.
DOI : 10.1016/j.jag.2013.02.002

M. Hosseini, Estimation of Leaf Area Index (LAI) in corn and soybeans using multi-polarization C- and L-band radar data, Remote Sensing of Environment, vol.170, pp.77-89, 2015.
DOI : 10.1016/j.rse.2015.09.002

X. Jin, Combined Multi-Temporal Optical and Radar Parameters for Estimating LAI and Biomass in Winter Wheat Using HJ and RADARSAR-2 Data, Remote Sensing, vol.7, issue.10, pp.13251-13272, 2015.
DOI : 10.3390/rs71013251

L. Dente, Assimilation of leaf area index derived from ASAR and MERIS data into CERES-Wheat model to map wheat yield, Remote Sensing of Environment, vol.112, issue.4, pp.1395-1407, 2008.
DOI : 10.1016/j.rse.2007.05.023

R. Fieuzal and F. Baup, Estimation of sunflower yield using multi-spectral satellite data (optical or radar) in a simplified agro-meteorological model, 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp.4001-4004, 2015.
DOI : 10.1109/IGARSS.2015.7326702

F. Baup, R. Fieuzal, and J. Betbeder, Estimation of soybean yield from assimilated optical and radar data into a simplified agrometeorological model, 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp.3961-3964, 2015.
DOI : 10.1109/IGARSS.2015.7326692

S. Moulin, A. Bondeau, and R. Delecolle, Combining agricultural crop models and satellite observations: From field to regional scales, International Journal of Remote Sensing, vol.19, issue.6, pp.1021-1036, 1998.
DOI : 10.1080/014311698215586

M. Guérif and C. L. Duke, Adjustment procedures of a crop model to the site specific characteristics of soil and crop using remote sensing data assimilation, Agriculture, Ecosystems & Environment, vol.81, issue.1, pp.57-69, 2000.
DOI : 10.1016/S0167-8809(00)00168-7

A. Olioso, 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.377-412, 2005.
DOI : 10.1007/s10795-005-8143-z

L. Midi-pyrénées, http://www.obs-mip. fr/services-observation/soa, Observatoire Spatial Régional (OSR)OSR, 2013.

C. Marais-sicre, F. Baup, and R. Fieuzal, Determination of the crop row orientations from Formosat-2 multi-temporal and panchromatic images, ISPRS Journal of Photogrammetry and Remote Sensing, vol.94, pp.127-142, 2014.
DOI : 10.1016/j.isprsjprs.2014.04.021

URL : https://hal.archives-ouvertes.fr/ird-01061256

F. Baup, MCM'10: An experiment for satellite multi-sensors crop monitoring from high to low resolution observations, 2012 IEEE International Geoscience and Remote Sensing Symposium, pp.4849-4852, 2012.
DOI : 10.1109/IGARSS.2012.6352527

H. Bleiholder, Growth stages of mono-and dicotyledonous plants, BBCH monograph Federal Biological Research Centre for Agriculture and Forestry, p.158, 2001.

E. Soil-bureau-working and . Group, Hydraulic properties of European soils (HYPRES), " Texture Classes, HYPRES Website, 1997.

A. Sand and H. De-boissezon, Reference remote sensing data bases: temporal series of calibrated and ortho-rectified satellite images for scientific use, 2nd Int. Symp. on Recent Advances in Quantitative Remote Sensing, 2006.

O. Hagolle, A multi-temporal method for cloud detection, applied to FORMOSAT-2, VEN??S, LANDSAT and SENTINEL-2 images, Remote Sensing of Environment, vol.114, issue.8, pp.1747-1755, 2010.
DOI : 10.1016/j.rse.2010.03.002

J. Liu, Quantifying crop biomass accumulation using multi-temporal optical remote sensing observations, 30th Canadian Symp. on Remote Sensing, 2009.

H. Mcnairn, ESTABLISHING CROP PRODUCTIVITY USING RADARSAT-2, ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol.8, p.8, 2012.
DOI : 10.5194/isprsarchives-XXXIX-B8-283-2012

. Betbeder, Contribution of multitemporal polarimetric synthetic aperture radar
URL : https://hal.archives-ouvertes.fr/hal-01331288

V. Demarez, Estimation of leaf area and clumping indexes of crops with hemispherical photographs, Agricultural and Forest Meteorology, vol.148, issue.4, pp.644-655, 2008.
DOI : 10.1016/j.agrformet.2007.11.015

URL : https://hal.archives-ouvertes.fr/hal-00287016

P. Dusseux, Combined Use of Multi-Temporal Optical and Radar Satellite Images for Grassland Monitoring, Remote Sensing, vol.6, issue.7, pp.6163-6182, 2014.
DOI : 10.3390/rs6076163

URL : https://hal.archives-ouvertes.fr/hal-01102961

W. Li, A Generic Algorithm to Estimate LAI, FAPAR and FCOVER Variables from SPOT4_HRVIR and Landsat Sensors: Evaluation of the Consistency and Comparison with Ground Measurements, Remote Sensing, vol.7, issue.12, pp.15494-15516, 2015.
DOI : 10.3390/rs71115494

URL : https://hal.archives-ouvertes.fr/hal-01271242

R. International, RADARSAT Data Product Specification, p.133, 2000.

E. Pottier and L. Ferro, PolSARPro V5.0: An ESA educational toolbox used for self-education in the field of POLSAR and POL-INSAR data analysis, 2012 IEEE International Geoscience and Remote Sensing Symposium, pp.7377-7380, 2012.
DOI : 10.1109/IGARSS.2012.6351925

URL : https://hal.archives-ouvertes.fr/hal-01130563

S. R. Cloude and E. Pottier, An entropy based classification scheme for land applications of polarimetric SAR, IEEE Transactions on Geoscience and Remote Sensing, vol.35, issue.1, pp.68-78, 1997.
DOI : 10.1109/36.551935

A. Freeman and S. L. Durden, A three-component scattering model for polarimetric SAR data, IEEE Transactions on Geoscience and Remote Sensing, vol.36, issue.3, pp.963-973, 1998.
DOI : 10.1109/36.673687

G. Cookmartin, Modeling microwave interactions with crops and comparison with ERS-2 SAR observations, IEEE Transactions on Geoscience and Remote Sensing, vol.38, issue.2, pp.658-670, 2000.
DOI : 10.1109/36.841996

J. W. Cable, Multi-Temporal Polarimetric RADARSAT-2 for Land Cover Monitoring in Northeastern Ontario, Canada, Remote Sensing, vol.6, issue.3, pp.2372-2392, 2014.
DOI : 10.3390/rs6032372

H. Yang, Potential of fully polarimetric SAR data for crops biophysical parameters retrieval, 2012 First International Conference on Agro- Geoinformatics (Agro-Geoinformatics), pp.1-5, 2012.
DOI : 10.1109/Agro-Geoinformatics.2012.6311620