Exploitation combinée de VENµS, Sentinel-2 and Landsat-8 : les bandes spectrales


L’utilisation combinée des données de VENµS, Sentinel-2 et Landsat-8 peut permettre d’augmenter la probabilité d’obtenir des images sans nuage ou de suivre de manière détaillée des phénomènes à évolution rapide.

Afin de faciliter cette combinaison, le tableau ci-dessous présente de manière résumée les correspondances entre les bandes spectrales des instruments. VENµS ne comporte pas de bande spectrale dans le moyen infrarouge.

La figure ci-dessous présente les bandes spectrales de VENµS et Sentinel-2 dans le domaine 400 à 1000 nm. Les bandes SWIR de Sentinel-2 ne sont incluses.Le tableau ci-dessous présente les combinaisons de bandes usuelles

La figure ci-après permet d'apprécier le degré de similarité des réponses spectrales de ces bandes usuelles.

Les réponses spectrales détaillées de chaque instrument sont disponibles via les pages web suivantes :











Didi Abuli (დიდი აბული) vu par Sentinel2-A

Le Didi Abuli domine la chaîne de montagne du petit Caucase en Géorgie. Ce secteur très peu fréquenté situé à proximité de la frontière Arménienne offre un terrain de jeu exceptionnel pour le ski de randonnée. Ainsi sur les traces des copains de la Timuzapata,  avec 2 collègues du Cesbio et 1 de l'ONERA, nous sommes allés arpenter les pentes de ce volcan endormi qui culmine à près de 3300m mais aussi découvrir l'hospitalité des habitants de cette région qui mérite vraiment de s'y attarder.
Oui mais quel rapport avec Sentinel2?

Trace de l'ascension du Didi Abuli-Sentinel-2A-2017-06-03

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La neige du Haut-Atlas marocain vue par Sentinel-2 et MODIS

Il était une fois, un jeune thésard qui se promenait dans les montagnes enneigées du Haut-Atlas avec un groupe d’amis. Pendant que ces derniers s’amusaient à prendre des selfies avec la neige il pensait à un autre type de selfies ! Il pensait aux photos de la Terre prises par les satellites : ces images refléteront-elles la beauté de cet endroit ? Leur résolution spatiale permettra-t elle de reproduire les subtilités de l’enneigement dans ce massif escarpé ?


Photo du Haut Atlas marocain prise à Oukaimeden. L’enneigement varie fortement selon la pente et l’orientation du terrain.

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Patagonian skies are not cloudy anymore

"The most usual weather in these latitudes is a fresh wind between north west and south west with a cloudy overcast sky" - Phillip Parker King, Sailing Directions for the Coasts of Eastern and Western Patagonia (1832).


Patagonia is a beautiful place to visit but campers know that the weather is extremely variable and the sky is often cloudy. This can be a problem for glaciologists, too, since they rely on optical satellite imagery to study glacier area changes over the last decades (mainly Landsat). Clear-sky optical images can also be used to determine glacier velocity, albedo, front variations, etc.
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Sentinel-2A captures a giant ice avalanche in Tibet

The Nature News website reported yesterday on a massive ice avalanche that happened in Rutog, Tibet, on 17 July 2016. This ice avalanche killed 9 people and may be one the largest ever observed. The ice and rock mixture spread over 6 km from the collapse point up to the Aru Co lake shoreline.

Sentinel-2A image of the Rutog ice avalanche acquired on 21-Jul-2016 (4 days after the event). Click on the image to see at full resolution (1 pixel = 10m).

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First Sentinel-2 snow map



In the framework of the THEIA land data center, we have developed a simple but robust method to map the snow cover from Sentinel-2-like level 2A products. This code was tested with SPOT-4 Take-5 and Landsat-8 series, but it remained to adapt it so that it can run on real Sentinel-2 images! This is now done thanks to Manuel Grizonnet, which allowed us to process the Sentinel-2A image acquired on 06-July-2015 in the Pyrenees as a first example. This image was produced at level 2A by Olivier Hagolle using the MACCS processor. The snow mask from Sentinel-2 images is calculated at 20 m resolution after resampling the green and red bands that are originally at 10 m resolution while the NIR band is at 20 m.

How to make sure everything went well? We can control the snow mask by superposing the mask boundaries on a false color composite:


The Sentinel-2A image of 06-July-2015 (level 2A, tile 30TYN) and its snow mask. The snow mask is in magenta and the background image is a color composite RGB NIR/Red/Green. We also show a zoom in the Vignemale area.

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Premier masque de neige Sentinel-2


Dans le cadre du Centre d'expertise scientifique THEIA "surface enneigée" nous avons développé une méthode simple et robuste pour détecter la neige à haute-resolution à partir des produits de niveau 2A de type Sentinel-2. Ce code a été testé sur des séries SPOT-4 Take-5 et Landsat-8, mais il restait à l'adapter pour qu'il puisse tourner sur de vraies images Sentinel-2 ! C'est chose faite grâce à Manuel Grizonnet, ce qui nous a permis de traiter l'image Sentinel-2A du 06-juillet-2015 sur les Pyrénées. Cette image avait été produite au niveau 2A par Olivier Hagolle avec la chaine MACCS. Le masque de neige est calculé à 20 m de résolution après ré-échantillonnage des bandes vertes et rouges qui sont d'origine à 10 m de résolution alors que la bande MIR est à 20 m. Continuer à lire

SAT-IRR: Satellite for Irrigation Scheduling


Following the irrigation scheduling experiment in Morocco during the SPOT4-Take5 experiment (Le Page et al, 2014), a Web tool owing to help the irrigation decision making is under development (http://osr-cesbio.ups-tlse.fr/Satirr). The tool is functional on three Landsat8 tiles: Marrakech in Morocco, Kairouan in Tunisia, Toulouse, France.


As the tool is addressing irrigators, the idea is to set an irrigated plot of the simplest and fastest possible way. After drawing his plot on a base map, the user answers to 4 questions. He chose his culture among 7 options currently parameterized (corn, wheat, olive ...), its soil among the 12 USDA typical soils, the sowing date and irrigation method (flooding, sprinkler or drip). This rough initialization is adequate launch the service although, at any time, the user can change the plot contours or refine parameterization if he knows the soils, the peculiarities of its crop, etc.


Screenshot from SAT-IRR web interface. The four icons allow modifying the plot parameters and contours, input irrigation, and consulting the results as graphs or tables. The graph results show a small Openlayers window with the last NDVI image, the sequence of NDVI thumbnail images, and 4 graphics: The “atmospheric part (rainfall, Reference Evapotranspiration and actual evapotranspiration), the second graph shows the status of the soil water content separated in three layers, the third graph shows the evolution of Basal Crop Coefficient and Fraction Cover, and the last graph is NDVI. The blue square at the right of the graphs are projections for the next month, including the green bars which are irrigation recommendations

Initially the server makes an approximation of an average behavior of the plant. For this, a monthly climatology is compiled (multi-annual average of weather parameters) and then interpolated to daily values, while the average behavior of the plant is extracted from FAO-56 Tables "FAO Irrigation and Drainage No. 56 : Guidelines for Computing Crop Water Requirements" (Allen et al, 1998). In a second step, the satellite images already on the server are examined and the relationship between NDVI and Basal Crop coefficient (Kcb) and percent of ground covered by vegetation (Fraction cover, Fc) are determined at each date by averaging on the plot.
Past weather is populated by measurements on the nearest synoptic station of the World Meteorological Organization and synthesized in the form of daily reference evapotranspiration (ET0) and rainfall. Forecasts are obtained by the API of the Norwegian Meteorological Institute.
Finally, a water balance very close to the one described in the FAO-56 is calculated by combining typical crop behavior and climate, satellite imagery, weather data and forecasts and projection into the future of crop development. The goal is to propose a date and dose of irrigation.


In addition to updating the weather (measures and forecasts), the server will check every day for the availability of new images (only Landsat8 for the time being). If there is availability, the tile is downloaded, it is then corrected for atmospheric effects using the information provided by the nearest photometer from the Aeronet network using the SMAC code (Rahman & Dedieu, 1994), then a cloud mask is created and NDVI is calculated. This image is stored as the original file is discarded to not overload the server.
All parameterization / measures / prediction are stored in a postgres / postgis database that links with a web client interface. The user can view the results in tables or graphs, and add its own irrigation in another dedicated interface.
While the interface is still a little rough, we are essentially considering developments on the server side:

  • Adaptation to Sentinel-2: the transition to S2 should not be a hassle. However, it will be necessary to adjust the calculation of the tiles to download, the download code and format reading.
  • Use of Sentinel-1: In the current state, the well-performance of water balance is based on the actual information of irrigation provided by the user. We plan to test the use of S1 images to determine the irrigation dates.
  • Access to local agro-weather stations: As part of the development of the Environmental Information System in Cesbio, telemetry of several weather stations has been settled up (eg, see http://trema.ucam.ac .ma) (Jarlan et al, 2015), we have to make these stations accessible through a standardized web service like Sensor Web.
  • Introduction of collective irrigation network. The PhD work of Kharrou (2013) and Belaqziz (2013, 2014) have shown that remote sensing can be used to optimize water rotations of an irrigated command. We plan to offer the possibility of introducing a set of plots to associate it with a distribution network and ultimately offer an optimized arrangement of the water rotation. However, at present, this goal is more into the order of a challenge!
  • We are currently working on a procedure to introduce wheat yield using remote sensing data (J. Toumi PhD Thesis) and further expect to input an early wheat yield prediction into the tool.

If you want to try it out, be my guest, it's free. If you want to try it out on other regions, please contact me!



  1. Le Page M., J. Toumi, S. Khabba, O. Hagolle, A. Tavernier, M. Kharrou, S. Er-Raki, M. Huc, M. Kasbani, A. Moutamanni, M. Yousfi, and L. Jarlan, “A Life-Size and Near Real-Time Test of Irrigation Scheduling with a Sentinel-2 Like Time Series (SPOT4-Take5) in Morocco,” Remote Sens., vol. 6, no. 11, pp. 11182–11203, Nov. 2014.
  2. Allen R., L. Pereira, D. Raes, and M. Smith, FAO Irrigation and Drainage n°56: Guidelines for Computing Crop Water Requirements, no. 56. FAO, 1998, pp. 273–282.
  3. Rahman H. and G. Dedieu, “SMAC: a simplified method for the atmospheric correction of satellite measurements in the solar spectrum,” Int. J. Remote Sens., vol. 15, no. 1, pp. 123–143, 1994.
  4. Kharrou M.H., M. Le Page, A. Chehbouni, V. Simonneaux, S. Er-Raki, L. Jarlan, L. Ouzine, S. Khabba, and A. Chehbouni, “Assessment of Equity and Adequacy of Water Delivery in Irrigation Systems Using Remote Sensing-Based Indicators in Semi-Arid Region, Morocco,” Water Resour. Manag., vol. 27, no. 13, pp. 4697–4714, Sep. 2013.
  5. Belaqziz S., S. Mangiarotti, M. Le Page, S. Khabba, S. Er-Raki, T. Agouti, L. Drapeau, M. H. Kharrou, M. El Adnani, and L. Jarlan, “Irrigation scheduling of a classical gravity network based on the Covariance Matrix Adaptation – Evolutionary Strategy algorithm,” Comput. Electron. Agric., vol. 102, pp. 64–72, Mar. 2014.
  6. Belaqziz S., S. Khabba, S. Er-Raki, L. Jarlan, M. Le Page, M. H. Kharrou, M. El Adnani, and A. Chehbouni, “A new irrigation priority index based on remote sensing data for assessing the networks irrigation scheduling,” Agric. Water Manag., vol. 119, pp. 1–9, Mar. 2013.
  7. Jarlan L., S. Khabba, S. Er-raki, M. Le Page et al, “Remote sensing of water resources in semi-arid Mediterranean basins: The Joint International Laboratory TREMA,” Int. J. Remote Sens., vol. (under review), 2015.



Dear reader,  may 2015 bring you health and happyness !

2015 should be a great year for the time series of optical images at a high resolution, with the launch of Sentinel 2A in Mat, in less than four months ! We have been waiting for it for so long that we can hardly believe it will be launched so soon. And to help you wait until then. SPOT5 orbit will be changed, to observe a hundred of sites with a 5 day repetitivity similar to that of Sentinel-2, until the end of August.


This post is also an opportunity to recall what was achieved in 2014 :

  • In February, we started the Sen2Agri project for l'ESA, with our partners, UCL, CS-SI France and CS-SI Romania. This project which is keeping us busy busy aims at producing a system for automatic classification of crops at the scale of whole countries.
  • In March, THEIA released a new version of SPOT4 (Take5) data, in particular with an enhanced geometrical superposition. This data set has now been downloaded by more than 600 users.
  • In May, the production in near real time (with a delay of 15 to 20 days) of LANDSAT 8 L2A products over France started (this type of product is still not available at USGS, but not for long, I guess...), followed by the processing of de 3 years of LANDSAT 5 & 7 data. 5 years of data, from 2009 to 2014, with an interruption in 2012, after LANDSAT 5 end of life and before LANDSAT 8 launch.
  • In September, CNES finally decided to launch SPOT5 (Take5) experiment,  thanks to a large contribution from ESA. The call for sites proposal was launched by ESA in November, and was largely successful, with 62 proposals for a hundred of sites. The analysis of this proposal is now on-going, and the choice will be difficult as the proposed applications are rich and very diverse.
  • In September too, CESBIO hosted the meeting of THEIA Scientific Expertise Centres, which allowed to identify about 20 products that the centre could prepare in the coming years. These products are described in the recent THEIA bulletin (in French).
  • In November, CNES hosted the SPOT4 (Take5) users meeting, to summarize data use, with a hundred of participants and  23 excellent presentations of the applications allowed by the experiment.
  • In December, we finally launched the call for sites proposal for Venµs mission, which will be launched in 2016. The deadline is January the 28th, 2015.


We will have several topics to comment for this blog that starts its third year, with a large audience : it received 23000 visits, and 47000 pages were read, a 50 % increase compared to last year. These weeks, it is getting harder for me to maintain a rhythm of a post per week that I tried to keep in the first two years. Contributions of data users are welcome !

In white, the countries from which no visit was observed in 2014 (Ouganda, Afghanistan)

Liste of the 10 countries from which the most frequent visits are observed.