The upcoming open-access Sentinel-2 Earth observation system should overcome this limitation because it will provide 10-m resolution satellite images with a 5-day frequency.Д¬oupling remote sensing data with crop model has been shown to improve accuracy of the model yield estimation. The main limitation is the acquisition of a minimum of five satellite images. Because this method is also the simplest to set up and requires less input data, it appears that it is the most suitable for performing operational estimations and forecasts of sugarcane yield at the field scale. Results showed that the linear empirical model produced the best results (RMSE = 10.4 t.ha(-1)). These models were compared with the crop model alone and discussed to provide recommendations for a satellite-based system for the estimation of yield at the field scale. We used a dataset of in-farm fields with contrasted climatic conditions and farming practices to compare three methods of yield estimation based on remote sensing: (1) an empirical relationship method with a growing season-integrated Normalized Difference Vegetation Index NDVI, (2) the Kumar-Monteith efficiency model, and (3) a forced-coupling method with a sugarcane crop model (MOSICAS) and satellite-derived fraction of absorbed photosynthetically active radiation. The estimation method selected here should also be exported to other sugarcane smallholder countries, particularly with introduction of the Sentinel-2 system to provide open access and high spatial resolution images.Д®stimating sugarcane biomass is difficult to achieve when working with highly variable spatial distributions of growing conditions, like on Reunion Island.

These results offer several prospects: firstly, a better inclusion of the heterogeneity of cultivars used on Reunion Island by recalibrating the key parameters of the yield computation for each of these cultivars in order to test various scenarios of cultivar implantation as a function of climatic zones of the island. We therefore recommend using the simple empirical relationship between yield and vegetation indices for the estimation of the sugarcane biomass on Reunion Island. Concerning the application approach, our results also showed that the more complex methods of yield estimation do not provide the best results when considering the precision. Finally, we determined an optimized value of the rooting depth parameter using recalibration and the water stress index CWSI as an adjustment variable. We also recalibrated the radiation use efficiency parameter for each studied cultivar. In particular, we showed that forcing the model resulted in a gain of accuracy of 2.6 t ha-1. Concerning the methodological approach, obtained results showed that remote sensing data, through a better inclusion of the actual state of development of the crop or an optimized parameterization of the model, results in a significant enhancement of the estimation of the yield by the MOSICAS model. Our dataset was composed of remote sensing data (SPOT4 & 5 images and thermal infrared data), yield data, climatic data, soil data and cropping practices data (irrigation schedules and harvest dates). Our tests were made on sixty three fields located on two contrasted in-farm sites, and on seven plots located on an experimental site. The MOSICAS sugarcane dedicated crop model, which is adapted to the cropping conditions of Reunion Island, was used. We organized our work in two main approaches: first, a methodological approach, where we explore the coupling (recalibration and forcing) between remote sensing data and modeling, and second, an operational approach where we compare three methods of yield estimation based on remote sensing : (1) empirical relationships between yield and vegetation indices computed from remote sensing data, (2) the efficiency models, with a low number of parameters and thus easily adaptable to different types of crops and (3) forcing a sugarcane crop growth model with data derived from remote sensing. The objective of this thesis is to explore the contribution of remote sensing for the estimation of sugarcane yields at field scale on Reunion Island.

In the context of an increasing demand for sugar, the estimation of sugarcane biomass in smallholding farming countries (of which Reunion Island is an example) is an optimization lever of production and thus of sustainability for the sugar industry facing giants such as Brazil, India of China.

Calculer un rendement locatif