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In semi-arid areas, it can be challenging to monitor the crop canopy and the production capacity of plants, especially cereals. In this context, the aim of the present study is to analyze the characteristics of cereals. Firstly, statistical analysis is used to characterize the vegetation's dynamics and grain yield, based on remotely sensed (satellite) Normalized Difference Vegetation Index (NDVI) measurements extracted from optical satellite SPOT/HRV images. Different robust relationships are established between satellite NDVI and straw yields for cereals. After validation of the approaches, a mapping of yields is proposed The second approach is based on the application of a SAFY "Simple Algorithm For Yield estimation" model, developed to simulate the dynamics of the LAI and the grain yield Inter-comparison between ground yield measurements and SAFY simulations show an over-estimation of this model. Finally, a coupling between satellite multi-temporal measurements and SAFY modeling is also proposed for yield mapping.