Sentinel-2 Agriculture

We are very proud to tell that our consortium was selected by ESA for the S2-Agri call for tender.


Our consortium is built from the following partners :


The S2-Agri project, whose website was just created, aims at showing on a large scale project, the capabilities of Sentinel-2 mission for agriculture monitoring, by providing, after consulting several "champion" users, and open source processing software, that will provide the following types of products :


  • periodic synthese of surface reflectances (Level 3A products)
  • a crop mask
  • a map of the main crops (see the image below, and the post on land cover maps)
  • some vegetation indices or biophysical variables

Example of a land cover map automatically generated by a software developed by Isabel Rodes (CESBIO), from LANDSAT 5 and 7 data in 2010. This land cover map was produced by I. Rodes, in the framework of a methodological PhD thesis, it is not as specialized for Agriculture as the ones that will be produced for S2-Agri project. It still already provides 3 agriculture classes : winter crops, summer corps, and meadows.


This project, which started on January 31st, 2014, will be carried out in three phases, each with an approximative duration of 1 year.

  1. A test phase, to develop, tune and validate methods and products, on 13 sites scattered around the world, this phase will mainly rely on SPOT4-Take5 data, complemented by LANDSAT 8 or RapidEye images. Several sites will be selected within the JECAM network.
  2. A development phase, during which the production system will be built, and prototype products will be issued and tested.
  3. A demonstration phase, based on the first year of Sentinel-2 acquisitions, for which 3 entire countries (> 500 000 km²) plus 5 sites of 300x3000 km². At least 2 of selected  the countries are in Africa.

At the end of the project, the production system will be released as an open source software by ESA, and

A l'issue de ce projet, le système de production sera disponible en open source auprès de l'ESA, and given the amount of work, we will have won dark circles around our eyes!


Sentinel-2 - Agriculture


Nous sommes très fiers d'annoncer que notre consortium vient de remporter l'appel d'offres S2-Agri de l'ESA.

Ce consortium est constitué par les entités suivantes :

Ce projet, dont le site officiel vient d'être créé, a pour but de mener une démonstration à grande échelle de l'intérêt du projet Sentinel-2 pour le suivi de l'agriculture, en fournissant, après consultation d'un grand nombre de "champion users", un logiciel libre de traitement, permettant d'obtenir des produits tels que :

  • des synthèses périodiques de réflectances de surface (produits de Niveau 3A)
  • un masque des cultures
  • une carte des principaux types de cultures (cf illustration ci-dessous, et voir l'article sur les cartes d'occupation des sols)
  • des indices de végétation ou des variables biophysiques

Exemple de classification réalisée automatiquement par Isabel Rodes (CESBIO), à partir de données LANDSAT 5 et 7 acquises en 2010. Cette carte d'occupation des sols, réalisée dans le cadre d'une thèse méthodologique, n'est pas spécialisée sur l'agriculture, contrairement à celles qui seront générées pour le projet S2-Agri, mais elle fournit déjà trois classes agricoles :cultures d'été, cultures d'hiver et prairies.


Ce projet, qui a démarré le 31/01/2014, se déroulera en trois phases d'une durée approximative d'un an chacune :

  1. Une phase de test et de mise au point des méthodes et produits, sur 13 sites distribués à travers le monde, qui s'appuiera sur des données SPOT4-Take5, complétées éventuellement par des données LANDSAT 8 ou RapidEye. Plusieurs sites feront partie du réseau JECAM.
  2. Une phase de développement du système de production, avec la génération et la validation des produits prototypes à partir des données acquises et pré-traitées durant la première année
  3. Une phase de démonstration, basée sur la première année d'acquisitions de Sentinel-2, pour laquelle 3 pays entiers (de la taille de la France) devront être traités, plus 5 sites de grande taille (300*300 km²) ! Au moins deux des trois pays sélectionnés seront situés en Afrique.

A l'issue de ce projet, le système de production sera disponible sous la forme d'un logiciel libre, auprès de l'ESA, et vue l'ampleur de la tâche, nous aurons gagné de beaux cernes sous les yeux.


The level 3A products

Among the products prepared to be processed by the THEIA land data center, the level 3A product was not yet described in this blog. The level 3A products provide a monthly synthesis of the level 2A. These products should be very useful for the following reasons :

  • The level 3A, produced once a month, uses up to six times less volume than the level 2A products acquires during a month.
  • The level 3A provides a regular time sampling of the reflectances variation, while the level 2A sampling is dependent on the cloud cover
  • Several processing methods and applications are hindered by the data gaps due to cloud cover. The level 3A product aims at minimizing the residual gaps.


Thanks to SPOT4 (Take5) data set, we were able to try and test several methods to produce level 3A products on varous types of landscapes and climates. This work, suprvised by Mireille Huc and myself, is performed by Mohamed Kadiri, at CESBIO, and is funded by the CNES budget of THEIA Land Data Center. Our method consists in computing, foe each pixel, a weighted average of the surface reflectances of the cloud free observations, obtained within a N day distance frome the central date TO of the level 3A product. For instance, the example below was obtained with N=21, for the 15 th of each month. As a result, the level 2A used in the average for the level 3A product dated on March the 15th, were acquired from Feruary the 24th to April the 4th.



The weighted average gives more weight to

  • the cloud free images
  • the pixels which are far from clouds
  • the images with a low aerosol content
  • the images acquired near the level 3A product date.

Les values of the weight and of the duration N, have a large influence on the product data quality. To tune their values, we set up three quality criteria :

  • The percentage of residual data gaps for which all the observations were cloudy
  • The difference of the level 3A reflectances with the values of a selected level 2A product acquired near the central date T0.
  • A measurement of the artefacts standard deviation. The artefacts appear near the borders of data gaps that affect one of the dates used in the level 3A synthesis.


For instance, here are the performances obtained on the Versailles site, which was heavily clouded in the spring of 2013. For this site, one can note, that the residual gap percentage is very low despite the bad weather, confirming that Sentinel-2 should be able to provide cloud free Level 3A products each month. For this site, the optimal duration of the synthesis is somewhere between 2* 21 and 2*28 days.


Performances obtained for Versailles SPOT4(Take5) site, for several values of the half-period N. In red, the residual percentage of data gaps (scale on the right), in yellow and green, the maximum value of the difference of the level 3A to the central level 2A, for resp the best 70% and 95% of pixels. In blue, the residual error standard deviation.




For Sentinel-2, the level 3A will have to include a correction for directional effects, in order to use in the same level 3A product, the data acquired from different satellite tracks, from different viewing angles. Finally, as an option, we might include a gap-filling method to fill the residual gaps.

In short, we still have work to do. A comparison with the classical NDVI Maximum Value Composite is provided in this post.