نبذة مختصرة : 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. 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. 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 MOSICAS sugarcane dedicated crop model, which is adapted to the cropping conditions of Reunion Island, was used. Our tests were made on sixty three fields located on two contrasted in-farm sites, and on seven plots located on an experimental site. 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). 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. In particular, we showed that forcing the model resulted in a gain of accuracy of 2.6 t ha-1. We also recalibrated the radiation use efficiency parameter for each studied cultivar. Finally, we determined an optimized value of the rooting depth ...
No Comments.