=> My colleagues at CESBIO are extremely creative! Over the past ten years, they have developed a wide range of new products and methods for extracting information from Copernicus data. They don’t just develop and validate the method on a few sites; they continue their work until they have produced data for the whole of […]
=> Mes collègues du CESBIO sont très créatifs ! Ils ont mis au point, au cours des dix dernières années, un grand nombre de nouveaux produits et de méthodes d’extraction de l’information à partir des données Copernicus (Sentinel-1 et 2). Et bien souvent, ils ne s’arrêtent pas à la mise au point de la méthode […]
This blog post is not a review of the excellent and deeply philosophical, parallel-universes delirium movie by Daniel Kwan and Daniel Scheinert, but the title of this drama resonates with the capabilities of our latest algorithm, which has just been published in Remote Sensing of Environment: J. Michel and J. Inglada, « Temporal attention multi-resolution fusion […]
After SMOS in 2009, and VENµS in 2017, the CESBIO laboratory is very proud to see its third proposed mission, Biomass, reach orbit. As always, it has been a long journey from the idea, at the beginning of the century, to the selection in 2013 as the seventh Earth Explorer Mission by ESA, to the […]
=> In arid or semi-arid regions, where irrigation is widespread, monitoring agricultural water resources is essential to anticipate shortages. These resources may come from large dams, small reservoirs, or groundwater aquifers. This is the case in the state of Telangana, in South India, where numerous large dams (shown in cyan blue in the figure below) […]
The results presented in this blog are based on the published work : I.Dumeur, S.Valero, J.Inglada « Self-supervised spatio-temporal representation learning of Satellite Image Time Series » in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, doi: 10.1109/JSTARS.2024.3358066. In this paper, we describe a self-supervised learning method to train a deep neural network […]
Contexte scientifique Le projet SOCCROP, qui a été financé par l’association Planet A, avait pour objectif de développer un indicateur pour quantifier les échanges annuels de CO2 entre les parcelles cultivées et l’atmosphère. Mesurer les flux permet d’accéder à l’évolution des stocks de carbone des sols agricoles. Cet indicateur peut être utile dans différents contextes […]
=> Claire Pascal, PhD student at CESBIO, under the supervision of Olivier Merlin (CNRS researcher) and Sylvain Ferrant (IRD researcher) brilliantly defended her thesis on the monitoring of water resources by satellite on November 18. Claire’s work focused on the Telangana region of India where rainfed cotton and flooded rice farming dominate. The region has […]
=> Claire Pascal, doctorante au CESBIO, sous la direction d’Olivier Merlin (chercheur CNRS) et co-dirigée par Sylvain Ferrant (chercheur IRD) a brillamment soutenu sa thèse sur le suivi des ressources en eau par satellite le 18 novembre. Les travaux de Claire se sont focalisés sur la région du Telangana en Inde où la culture non […]