In climate change context, crop production assessment is a worldwide issue for agriculture that can be addressed using crop models like STICS, which simulate plant-environment interactions. Calibrating cultivar parameters is a key preliminary step that requires a substantial amount of field data, which might be a constraint for operational application. The objective of this work is to propose a methodology for calibrating STICS plant parameters using remote sensing and information from farm (soil, management, yield). The methodology was applied to spring wheat varieties (Triticum aestivum L.) grown in the Central Plateau of Spain. To avoid confusions between genetic traits and impact of edaphic stresses, the calibration was done on well irrigated and fertilized fields, while the validation encompassed a wider range of conditions. Green area index (GAI RS ) time series computed on multispectral Sentinel-2 and Landsat 8 satellite images were used to characterize leaf cover development and phenology. The results led to rmse ranging between 6 and 14 days for the different phenological stages simulated by STICS, 1.3 m 2 m -2 for GAI and 1.7 t ha -1 for yield. These results were found better than using an existing parameterization established using large experimental data sets on a similar spring wheat cultivar. The evaluation of the calibrated crop model on water-stressed conditions was satisfactory showing the ability of the STICS crop model to represent environmental stresses even though the model was calibrated under optimal conditions. The adding value of using field phenological observations was marginal while calibration on biomass observations was required to accurately simulate biomass. However, it has been shown that a biased biomass simulation had little impact on yield and GAI. This work shows that by using readily available data such as data recorded by farmers or derived from remote sensing, it is possible to calibrate the plant parameters of a crop model leading to yield and GAI simulations better than those computed with existing set of plant parameter calibrated on comparable varieties