R. Marteau, B. Sultan, V. Moron, A. Alhassane, C. Baron et al., The onset of the 648 rainy season and farmers' sowing strategy for pearl millet cultivation in Southwest Niger

, For. Meteorol, vol.151, issue.10, pp.1356-1369, 2011.

. Fao, 2014-2016 strategic response plan : Sahel region, 2014.

P. B. Akponikpè, J. Minet, B. Gérard, P. Defourny, and C. L. Bielders, Spatial fields ' 652 dispersion as a farmer strategy to reduce agro-climatic risk at the household level in pearl millet653 based systems in the Sahel : A modeling perspective, Agric. For. Meteorol, vol.151, pp.215-654, 2011.

S. B. Traoré, A. Alhassane, B. Muller, M. Kouressy, L. Somé et al., , p.656

S. Laopé, M. Sangaré, M. Vaksmann, M. Diop, C. Dingkuhn et al., Characterizing and 657 modeling the diversity of cropping situations under climatic constraints in West Africa

, Sci. Lett, vol.12, issue.1, pp.89-95, 2011.

C. Justice and I. Becker-reshef, Developing a strategy for global agricultural monitoring in the 660 framework of Group on Earth Observations (GEO) Workshop Report, 2007.

M. Meroni, D. Fasbender, F. Kayitakire, G. Pini, F. Rembold et al., Early 662 detection of biomass production deficit hot-spots in semi-arid environment using FAPAR time 663 series and a probabilistic approach, Remote Sens. Environ, vol.142, pp.57-68, 0664.

M. A. White, P. E. Thorton, and S. W. Running, A continental responses phenology model 665 climatic for monitoring variability vegetation to interannual, vol.11, p.666, 1997.

J. Huang and D. Han, Meta-analysis of influential factors on crop yield estimation by remote 667 sensing, Int. J. Remote Sens, vol.35, issue.6, pp.2267-2295, 2014.

N. T. Son, C. F. Chen, C. R. Chen, L. Y. Chang, H. N. Duc et al., Prediction of rice 669 crop yield using MODIS EVI?LAI data in the Mekong Delta, Int. J. Remote Sens, vol.670, issue.20, pp.7275-7292, 0671.

C. J. Tucker, C. Vanpraet, E. Boerwinkel, and A. Gaston, Satellite remote-sensing of total dry672 matter production in the Senegalese Sahel, Remote Sens. Environ, vol.13, issue.6, pp.461-474, 1983.

C. J. Tucker, Satellite Remote Sensing of Total Herbaceous Biomass Production in the Senegalese 675 Sahel : 1980-1984, Remote Sens. Environ, vol.17, pp.233-249, 1985.

S. D. Prince, M. J. Eden, and J. T. Parry, Monitoring the vegetation of semi-arid tropical 677 rangelands with the NOAA-7 Advanced Very High Resolution Radiometer," in Remote sensing 678 and tropical land management, pp.307-334, 1986.

I. Becker-reshef, E. F. Vermote, M. Lindeman, and C. Justice, A generalized regression-based 680 model for forecasting winter wheat yields in Kansas and Ukraine using MODIS data, p.681

, Sens. Environ, vol.114, issue.6, pp.1312-1323, 2010.

A. K. Prasad, L. Chai, R. P. Singh, and M. Kafatos, Crop yield estimation model for Iowa using 683 remote sensing and surface parameters, Int. J. Appl. Earth Obs. Geoinf, vol.8, pp.26-33, 2006.

M. S. Rasmussen, Assessment of millet yields and production in northern Burkina Faso using 685 integrated NDVI from the AVHRR, Int. J. Remote Sens, vol.13, issue.18, p.686, 1992.

M. S. Rasmussen, Operational yield forecast using AVHRR NDVI data: Reduction of 687 environmental and inter-annual variability, Int. J. Remote Sens, vol.18, issue.5, pp.1059-1077, 1997.

A. M. Sibley, P. Grassini, N. E. Thomas, K. G. Cassman, and D. B. Lobell, Testing Remote 690 Sensing Approaches for Assessing Yield Variability among Maize Fields, Agron. J, vol.106, issue.691, p.24, 2014.

C. Yang, J. H. Everitt, and J. M. Bradford, Evaluating high resolution SPOT 5 satellite imagery to 693 estimate crop yield, Precis. Agric, vol.10, issue.4, pp.292-303, 2009.

F. Rembold, C. Atzberger, I. Savin, and O. Rojas, Using Low Resolution Satellite Imagery for 695 Yield Prediction and Yield Anomaly Detection, Remote Sens, vol.5, issue.4, pp.1704-1733, 2013.

D. B. Lobell, The use of satellite data for crop yield gap analysis, F. Crop. Res, vol.143, pp.698-56, 2013.

M. S. Moran, Y. Inoue, and E. M. Barnes, Opportunities and Limitations for Image-Based 700

, Remote Sensing in Precision Crop Management, Remote Sens. Environ, vol.61, pp.319-346, 1997.

L. Wall, D. Larocque, and P. Léger, The early explanatory power of NDVI in crop yield 703 modelling, Int. J. Remote Sens, vol.29, issue.8, pp.2211-2225, 2008.

C. J. Tucker, Red and Photographic Infrared linear Combinations for Monitoring Vegetation, 705 Remote Sens. Environ, vol.8, pp.127-150, 1979.
DOI : 10.1016/0034-4257(79)90013-0

B. N. Holben, C. J. Tucker, and C. J. Fan, Spectral assessment of soybean leaf area and leaf 707 biomass, Photogramm. Eng. Remote Sensing, vol.46, pp.651-656, 1980.

J. L. Hatfield, E. T. Kanemasu, G. Asrar, R. D. Jackson, P. J. Pinter et al., Leaf-area estimates from spectral measurements over various planting dates of wheat, Int. J. 710 Remote Sens, vol.709, pp.651-656, 1984.

F. Maselli, S. Romanelli, L. Bottai, and G. Maracchi, Processing of GAC NDVI data for yield 712 forecasting in the Sahelian region, Int. J. Remote Sens, vol.21, issue.18, p.713, 2000.

F. Maselli and F. Rembold, Analysis of GAC NDVI Data for Cropland Identification and Yield 714 Forecasting in Mediterranean African Countries, Photogramm. Eng. Remote Sensing, vol.67, issue.715, pp.593-602, 2001.

S. M. Groten, NDVI-crop monitoring and early yield assessment of Burkina Faso, Int. J. 717 Remote Sens, vol.14, issue.8, pp.1495-1515, 1993.

J. L. Monteith and C. J. Moss, Climate and the efficiency of crop production in Britain

, Trans. R. Soc. Lond. B. Biol. Sci, vol.281, issue.980, pp.277-294, 1977.

J. L. Monteith, Solar radiation and productivity in tropical ecosystems, J. Appl. Ecol, vol.9, issue.721, pp.747-766, 1972.

R. B. Myneni and D. L. Williams, On the relationship between FAPAR and NDVI

. Environ, , vol.49, pp.200-211, 1994.

J. Lecoeur and T. R. Sinclair, Harvest index increase during seed growth of field pea, Eur. J. 725 Agron, vol.14, issue.3, pp.173-180, 2001.

R. L. Delougherty and R. K. Crookston, Harvest Index of Corn Affected by Population Density, 727 Maturity Rating, and Environment, Agron. J, vol.71, issue.4, pp.577-580, 1979.

M. Unkovich, J. Baldock, and M. Forbes, Chapter 5-Variability in Harvest Index of Grain Crops 729 and Potential Significance for Carbon Accounting: Examples from Australian Agriculture, 730 Advances in Agronomy, vol.105, pp.173-219, 2010.

A. N. Misra, Assimilate partitioning in pearl millet (Pennisetum glaucum L.R.Br.), Acta Physiol. 732 Plant, vol.17, issue.1, pp.41-46, 1995.

S. B. Idso, R. D. Jackson, and R. J. Reginato, Remote-sensing of crop yields, vol.734, pp.19-25, 1977.

R. C. Smith and H. ,

J. Barrs,

M. Steiner and . Stapper, Relationship between wheat yield and 736 foliage temperature: theory and its application to infrared measurements, Agric. For. Meteorol, vol.737, issue.2, pp.129-143, 1985.

R. D. Jackson, S. B. Idso, R. J. Reginato, and P. J. Pinter, Canopy temperature as a crop water 739 stress indicator, Water Resour. Res, vol.17, issue.4, pp.1133-1138, 1981.

P. J. Pinter, K. E. Fry, G. Guinn, and J. R. Mauney, Infrared thermometry: A remote sensing 741 technique for predicting yield in water-stressed cotton, Agric. Water Manag, vol.6, issue.4, pp.742-385, 1983.

D. F. Wanjura, J. L. Hatfield, and D. R. Upchurch, Crop water stress index relationships with crop 744 productivity, Irrig. Sci, vol.11, issue.2, pp.93-99, 1990.

A. E. Ajayi and A. A. Olufayo, Evaluation of Two Temperature Stress Indices to Estimate Grain 746

, Sorghum Yield and Evapotranspiration, Agron. J, vol.96, issue.5, pp.1282-1287, 2004.

N. K. Gontia and K. N. Tiwari, Development of crop water stress index of wheat crop for 748 scheduling irrigation using infrared thermometry, Agric. Water Manag, vol.95, issue.10, pp.1144-749, 2008.

M. Dingkuhn, C. Baron, V. Bonnal, F. Maraux, B. Sarr et al., Decision 751 support tools for rainfed crops in the Sahel at the plot and regional scales," in Decision support 752 tools for smallholder agriculture in Sub-Saharan Africa : A practical guide, Muscle Sho, pp.127-139, 2003.

L. Hatfield, Remote Sensing Estimators of Potential and Actual Crop Yield, Remote Sens. 755 Environ, vol.13, pp.301-311, 1983.

T. R. Sinclair, C. B. Tanner, and J. M. Bennett, Water-Use Efficiency Crop Production, 757 Bioscience, vol.34, issue.1, pp.36-40, 1984.

B. Sultan, C. Baron, M. Dingkuhn, B. Sarr, and S. Janicot, Agricultural impacts of large-scale 759 variability of the West African monsoon, Agric. For. Meteorol, vol.128, issue.1-2, p.760

L. , L. Barbé, and T. Lebel, Rainfall climatology of the HAPEX-Sahel region during the years 762 1950-1990, J. Hydrol, pp.43-73, 1997.

P. Hiernaux, A. Ayantunde, A. Kalilou, E. Mougin, B. Gérard et al., Trends in productivity of crops , fallow and rangelands in Southwest Niger : Impact of land use , 765 management and variable rainfall, J. Hydrol, vol.764, issue.1-2, pp.65-77, 2009.

J. Rockström and A. De-rouw, Water , nutrients and slope position in on-farm pearl millet 767 cultivation in the Sahel, Plant Soil, vol.195, pp.311-327, 1997.

C. Baron, B. Sultan, M. Balme, B. Sarr, S. B. Traoré et al., From GCM grid cell to agricultural plot: scale issues affecting modelling of climate impact, Philos. Trans. R. Soc. Lond. B. Biol. Sci, vol.769, issue.1463, pp.2095-2108, 2005.
URL : https://hal.archives-ouvertes.fr/hal-00122721

C. Justice, E. F. Vermote, J. Townshend, R. S. Defries, D. P. Roy et al., , p.772

J. L. Privette, G. Riggs, A. H. Strahler, W. Lucht, R. Myneni et al.,

A. Nemani, W. Huete, R. E. Van-leeuwen, L. Wolfe, J. Giglio et al., , p.774

. Barnsley, The Moderate Resolution Imaging Spectroradiometer (MODIS): land remote sensing 775 for global change research, IEEE Trans. Geosci. Remote Sens, vol.36, issue.4, pp.1228-1249, 1998.

A. Huete, K. Didan, T. Miura, E. Rodriguez, X. Gao et al., Overview of the 778 radiometric and biophysical performance of the MODIS vegetation indices

. Environ, , vol.83, pp.195-213, 2002.

J. Chen, P. Jönsson, M. Tamura, Z. Gu, B. Matsushita et al., A simple method for 781 reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter, 782 Remote Sens. Environ, vol.91, issue.3-4, pp.332-344, 2004.

Z. Wan, Modis Land Surface Temperature Products Users' Guide, 2013.

Z. Wan, Y. Zhang, Q. Zhang, and Z. Li, Quality assessment and validation of the MODIS 786 global land surface temperature, Int. J. Remote Sens, vol.25, issue.1, pp.261-274, 0787.

M. A. Friedl, D. Sulla-menashe, B. Tan, A. Schneider, N. Ramankutty et al., MODIS Collection 5 global land cover : Algorithm refinements and characterization of new 789 datasets, Remote Sens. Environ, vol.788, issue.1, pp.168-182, 2010.
DOI : 10.1016/j.rse.2009.08.016

M. A. Friedl, D. K. Mciver, J. C. Hodges, X. Y. Zhang, D. Muchoney et al.,

S. Woodcock, A. Gopal, A. Schneider, A. Cooper, F. Baccini et al., Global land 792 cover mapping from MODIS: Algorithms and early results, Remote Sens. Environ, vol.83, issue.1, pp.287-302, 2002.

B. Sultan, P. Roudier, P. Quirion, A. Alhassane, B. Muller et al., , p.795

S. B. Guimberteau, C. Traoré, and . Baron, Assessing climate change impacts on sorghum and 796 millet yields in the Sudanian and Sahelian savannas of West Africa, Environ. Res. Lett, vol.8, issue.797, p.9, 2013.

B. Sultan, K. Guan, M. Kouressy, M. Biasutti, C. Piani et al., Robust features of future climate change impacts on sorghum yields in West Africa, vol.799
URL : https://hal.archives-ouvertes.fr/hal-01317169

, Res. Lett, vol.9, p.13, 2014.

J. Ramarohetra, B. Sultan, C. Baron, T. Gaiser, and M. Gosset, How satellite rainfall estimate 802 errors may impact rainfed cereal yield simulation in West Africa, Agric. For. Meteorol, vol.180, pp.803-118, 2013.

S. Bassu, N. Brisson, J. Durand, K. Boote, J. Lizaso et al., , p.805

M. Adam, C. Baron, B. Basso, C. Biernath, H. Boogaard et al.,

,. S. De-sanctis, P. Gayler, J. Grassini, S. Hatfield, C. Hoek et al.,

K. C. Kemanian, S. H. Kersebaum, N. S. Kim, D. Kumar, C. Makowski et al.,

M. V. Priesack, F. Pravia, I. Sau, F. Shcherbak, E. Tao et al., How 809 do various maize crop models vary in their responses to climate change factors?, Glob. Chang. 810 Biol, vol.20, issue.7, pp.2301-2320, 2014.

M. Kouressy, M. Dingkuhn, M. Vaksmann, and A. B. Heinemann, Adaptation to diverse semi812 arid environments of sorghum genotypes having different plant type and sensitivity to 813 photoperiod, Agric. For. Meteorol, vol.148, issue.3, pp.357-371, 2008.

G. Bezançon, J. Pham, M. Deu, Y. Vigouroux, F. Sagnard et al., , p.815

B. Gérard, J. Ndjeunga, and J. Chantereau, Changes in the diversity and geographic distribution of 816 cultivated millet (Pennisetum glaucum (L.) R. Br.) and sorghum (Sorghum bicolor (L.) Moench) 817 varieties in Niger between, Genet. Resour. Crop Evol, vol.56, issue.2, pp.223-236, 1976.

P. Roudier, B. Sultan, P. Quirion, C. Baron, A. Alhassane et al., An ex820 ante evaluation of the use of seasonal climate forecasts for millet growers in SW Niger, Int. J. 821 Climatol, vol.32, pp.759-771, 2011.

M. Vaksmann and S. B. Traoré, Adéquation entre risque climatique et choix variétal du mil : Cas 823 de la zone de Bankass au Mali, Bilan hydrique agricole et sécheresse en Afrique Tropicale, p.824

J. Wiley, , pp.113-123, 1991.

F. Jrc, Harmonized World Soil Database (version 1.2)." FAO, Rome, 826 Italy and IIASA, 2012.

M. V. Sivakumar, Predicting rainy season potential from the onset of rains in Southern Sahelian 828 and Sudanian climatic zones of West Africa, Agric. For. Meteorol, vol.42, pp.295-305, 1988.

. Fao, Crop calendar-An information tool for seed security, 2010.

M. S. Moran, T. R. Clarke, Y. Inoue, and A. Vidal, Estimating Crop Water Deficit Using the 832 Relation between Surface-Air Temperature and Spectral Vegetation Index
DOI : 10.1016/0034-4257(94)90020-5

. Environ, , vol.49, pp.246-263, 1994.

R. Delécolle, S. J. Maas, M. Guérif, and F. Baret, Remote sensing and crop production models: 835 present trends, ISPRS J. Photogramm. Remote Sens, vol.47, issue.2-3, pp.145-161, 1992.

, Farmers yield variability assessment and validation of crop model to predict 'average 837 regional' farmers yield for the main cropped varieties of millet, sorghum and maize, p.838

. France, , 2009.

A. J. Challinor, T. R. Wheeler, P. Q. Craufurd, J. M. Slingo, and D. I. Grimes, Design and 840 optimisation of a large-area process-based model for annual crops, Agric. For. Meteorol, vol.841, issue.1-2, pp.99-120, 2004.

A. Bégué, J. F. Desprat, J. Imbernon, and F. Baret, Radiation use efficiency of pearl millet in the 843 Sahelian zone, Agric. For. Meteorol, vol.56, pp.93-110, 1991.

A. Huete and C. J. Tucker, Investigation of soil influences in AVHRR red and near-infrared 845 vegetation index imagery, Int. J. Remote Sens, vol.12, issue.6, pp.1223-1242, 1991.

A. Diouf and E. F. Lambin, Monitoring land-cover changes in semi-arid regions: remote sensing 847 data and field observations in the Ferlo, Senegal, J. Arid Environ, vol.48, issue.2, pp.129-148

C. J. Tucker and B. ,

J. Holben,

J. Elgin,

. Mcmurtrey, Relationship of spectral data to grain 850 yield variation, Photogramm. Eng. Remote Sensing, vol.46, issue.5, pp.657-666, 1980.

J. Huang, H. Wang, Q. Dai, and D. Han, Analysis of NDVI Data for Crop Identification and Yield 852 Estimation, IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens, vol.7, issue.11, pp.4374-4384, 2014.

E. Vintrou, A. Bégué, C. Baron, S. Alexandre, D. Lo-seen et al., A Comparative 855 Study on Satellite and Model-Based Crop Phenology in West Africa, Remote Sens, vol.6, pp.856-1367, 2014.

J. ,

G. Jones, C. Hoogenboom, and K. Porter,

W. Boote, L. Batchelor, P. Hunt, and U. Wilkens,

A. Singh, J. Gijsman, and . Ritchie, The DSSAT cropping system model, Eur. J. Agron, vol.859, issue.3-4, pp.235-265, 2003.

. Fao, A computer program for irrigation planning and management, vol.46, 1992.

J. L. Hatfield and M. S. Moran, Agriculture and Remote Sensing, pp.22-32, 2014.

F. Net, LIVELIHOODS ZONING ' PLUS ' ACTIVITY IN NIGER, 2011.

L. Leroux, A. Jolivot, A. Bégué, D. Lo-seen, and B. Zoungrana, How Reliable is the MODIS 866

, Land Cover Product for Crop Mapping Sub-Saharan Agricultural Landscapes?, Remote Sens, vol.867, issue.6, pp.8541-8564, 2014.

D. Lobell and C. Field, Global scale climate-crop yield relationships and the impacts of recent 869 warming, Environ. Res. Lett, vol.2, p.7, 2007.

J. N. Hird and G. J. Mcdermid, Noise reduction of NDVI time series : An empirical comparison 871 of selected techniques, Remote Sens. Environ, vol.113, pp.248-258, 2009.

L. Leroux, C. Baron, S. B. Traoré, D. Lo-seen, and A. Bégué, Testing satellite rainfall estimates 873 time series for crop yield simulation of a rainfed cereal in West Africa, 8th International 874 Workshop on the Analysis of Multitemporal Remote Sensing Images, 2015.