## [MUSCATE news] MAJA upgraded to version 2

Yesterday, the MUSCATE ground segment started delivering Sentinel-2A L2A products using the MAJA V2 processor, while MAJA V1 was used until now. MAJA V2 corrects for a few bugs (such as the pixels flagged as cloud or cloud shadow on the edge of the images) and adds three new features :

• We implemented a correction for directional effects for a better estimate of Aerosol optical thickness. As you probably know, MAJA uses multi-temporal criteria to detect clouds and estimate aerosol content. These criteria suppose that surface reflectance does not change much from one date to the next one. Over a given tile, we can combine data coming from two adjacent orbits, with slightly different viewing angles, and the directional effect can induce some variations in the surface reflectance of successive acquisitions, which would be interpreted as atmospheric effects. We are now using a simple directional correction to reduce this noise source (D.Roy et al). As this directional correction is not perfectly accurate, it is not applied to the surface reflectance we deliver at the end of MAJA processing.

Elsa Bourgeois, from Cap Gemini, compared the performances of processing with or without directional correction. In both cases (S2A, top, S2B, bottom), there is only a very slight improvement of performances.

• We implemented a cirrus correction, that comes from DLR works. This correction is not in production yet, as it needs more validation on a large data set. We simply parametrise MAJA with "cirrus_correction= false". A coming post will address this subject.
• We have started using the new high cloud threshold that was refined in this post. It will result in more cloud cover, with a large difference over mountains.

All these small improvements are now implemented in version 1.6. They do not justify a reprocessing of the Sentinel-2 archive, although the accumulation of successive slight improvement could justify it. We intend to start a reprocessing when MAJA V3 is put in production.

## Systematic validation of Sentinel-2 THEIA L2A products

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Very recently, Camille Desjardins (from CNES), who is handling the validation of the L2A products generated by THEIA, has set up a systematic validation of the products delivered by MAJA, with the help of an operational service from CNES (OT/PE) (Bruno Besson, and Nicolas Guilleminot from Thales Services, using tools developed by Aurélie Courtois, also from Thales)

Systematically, a comparison of AOT and water vapour is made for every Sentinel-2 L2A product from THEIA which observes one of the sites of the Aeronet network.

Both plots below show the results obtained during the month of February, for the Aerosol Optical Thickness (left), and for the water vapour content (right). Blue dots correspond to validations in ideal conditions (low cloud amount, no gap filling, and quality assured Aeronet data (Level 2.0). The red dots allow degraded conditions, and most of them correspond to the unavailability, yet, of version 2.0 Aeronet data. As data are processed in near real time, and level 2.0 data are made available a few months later, these plots rely mainly on Level 1.5 data, which are more prone to errors (such as a calibration drift... or the presence of a spider in the instrument tubes).

 Aerosol optical thickness validation of Sentinel-2 L2A for all Aeronet match-ups gathered in February 2018 Water vapour validation of Sentinel-2 L2A for all Aeronet match-ups gathered in February 2018 (in g/cm2)

## [MUSCATE News] Reprocessing of Sentinel-2B data aquired from July to October 2017

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MUSCATE is in a good shape these days thznkd to the continuous efforts of the development team (CNES and CAP GEMINI) who solved several issues. The counter of Sentinel-2 Level 2A products reached 70 000 products this night, just one month after reaching 60000. If we sum all the products delivered by MUSCATE, we are reaching 99 000 images. MUSCATE also distributes Sentinel-2 Snow masks over mountains, and Spot World Heritage data (old SPOT data reprocessed after ortho-rectification.and made available for free).

This good shape allows us to increase our production rhythm. We have started processing the Sentinel-2B data acquired between July and October 2017, as we had started processing S2B in November 2017 only. But since MAJA is a multi-temporal processor, we are in fact starting a complete reprocessing of the data, including S2A and S2B. The quality of S2A products should therefore also benefit from the improved repetitivity of observations.

This reprocessing will last several weeks. We are starting with data from France and will go on with our neighbouring European countries, then sites in Maghreb, the remaining sites of Africa, and finally, the rest of the sites in the world.

In case you have an urgent need for some tiles, please ask ! (of course, it is only applicable to the tiles already in our list)

## Amélioration de la détection des nuages hauts dans MAJA pour les images de Sentinel-2

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La recherche pour l'amélioration des performances des méthodes de MAJA repose actuellement sur une toute petite équipe au CESBIO, composée de deux personnes, Bastien Rouquié, qui travaille sur l'amélioration des estimations d'aérosols, et moi, qui passe presque tout mon temps en réunions, ou a écrire des articles de blog (et parfois les deux en même temps). C'est pour cette raison que de nombreux points que nous aimerions améliorer sur MAJA ne s'améliorent que lentement.

Absorption atmosphérique. En bleu, la réflectance de surface pour un pixel couvert de végétation, en fonction de la longueur d'onde, en rouge la réflectance au sommet de l'atmosphère pour ce même pixel. A 1.38 µm, la vapeur d'eau absorbe totalement la lumière provenant de la surface au niveau de la mer.

J'ai pu récemment consacrer un peu de temps à l'amélioration de la détection des nuages, notamment au dessus de l'eau, et plus récemment, à améliorer la détection des nuages hauts, en utilisant la  bande "cirrus" située à 1.38 µm, qui est disponible sur Sentinel-2 et Landsat 8. Comme précisé dans ce post, la bande "cirrus" est située dans une forte bande d'absorption de la vapeur d'eau, telle qu'au niveau de la mer, les photons ont très peu de chances de faire le parcours du soleil au satellite en passant par la surface de la terre sans être absorbés. Comme la majorité de la vapeur d'eau est située dans les basses couches de l'atmosphère, les nuages situés plus haut dans l'atmosphère ont davantage de chances de renvoyer de la lumière jusqu'au satellite. C'est donc un moyen de détecter les nuages hauts.

La méthode de détection parait donc très simple, il suffit de faire un seuillage sur la réflectance dans la bande 1.38 µm.  Malheureusement, c'est plus compliqué que ça.

## Theia produit au niveau 2A toute la bande côtière du Maghreb

Les tuiles en bleu viennent d'être ajoutées aux zones où Theia fournit des produits de niveau 2A.

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Depuis la découverte des récents bugs et la mise en place de moyens de les contourner, le rythme de  production de MUSCATE s'est accru, et nous avons donc pu étendre un peu les zones où nous fournissons des données Sentinel-2 (A&B) corrigées des effets atmosphériques, avec un bon masque de nuages: il s'agit de produits de niveau 2A fournis par la chaîne MAJA.

Nous venons de mettre en ligne toutes les données acquises sur la zone côtière du Maghreb, du Maroc à la frontière entre Algérie et Tunisie. Quelques tuiles manquantes ont également été rajoutées au sud du Maroc, et sur le Cap Bon, en Tunisie. Avec cet ajout de 50 tuiles, toutes les terres qui bordent la méditerranée occidentale sont donc suivies pat les produits de Theia (enfin, il manque les Baléares).

## [MUSCATE] Theia releases Sentinel-2 L2A products on the whole Maghreb coastal region

The blue tiles were just added to the zones where Theia provides level 2A products with MAJA.

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Since we understood the bugs which were slowing MUSCATE, and we found ways to mitigate them, the production rhythm of MUSCATE improved and we were able to extend the zones where we provide Sentinel-2 (A&B) L2A products. L2A products provide surface reflectances after correction of atmospheric effects and with a high quality cloud mask. The products we deliver are provided by MAJA processor.

We just released all the data acquired on the Maghreb coastal zone, from Morocco to Tunisia. A few missing tiles have also been added in South Morocco, and on Cap Bon in Tunisia. With these new tiles, we now monitor all the lands that surround the occidental part of Mediterranean sea, adding 50 tiles to those already processed.

## Improvements of MAJA cloud masks in production

We are continuously working on improving the Sentinel-2 L2A products delivered by Theia. Since the 2nd of February, a new parametrization was put in production in order to improve two points of the cloud masks. There is a page which summarizes the variations of Theia product versions. Because of some error within Muscate production centre, we are not able to change the product version when we change a parameter. You have to look at the production date to know which version was used. This inconvenience will be corrected soon.

### Clouds above water

Although MAJA is optimized for cloud detection and atmospheric correction over land, it is important to detect clouds well over water. For instance to detect the shadows of these clouds that are cast over land. But until now, the clouds mask was missing quite a lot of clouds over water. This was not a surprise as we had passed only a few hours determining the thresholds to apply. We recently found some more time to obtain a better tuning of the detection thresholds above water.

Thresholds in the SWIR have been halved (from 0.08 to 0.04), in the absence of sunglint. When sunglint is likely, due to the geometry of acquisition, the threshold is still higher (0.016, but it was 0.25 before).This means that when the sunglint flag is raised, the accuracy of cloud detection is reduced.

Impact of new cloud detection threshold over water : left, old threshold, right, new threshold.

### Cloud dilation

The plane contrail illustrates the difference in observation angles of the spectral bands of Sentinel-2. The cumulus clouds above has the same effect, although lower because the cloud is at a lower altitude.

As it may be seen on the image above, the cloud limits are fuzzy, and except for the big and nice cumulus clouds, the pixel next to the cloud mask is also affected by clouds. Even if the cloud has sharp limits, it also changes the illumination of neighbouring pixels, and, in the case of Sentinel-2, as all the bands do not observe exactly in the same direction, there is a "parallax effect" which results in different cloud positions depending on the spectral band. For all these reasons, we need to dilate the cloud mask (by the way, this is an identified drawback of Sen2cor, which does not dilates its clouds).

Our dilation buffer was originally 480m. Following complaints from some users working in very cloudy countries, we had reduced the buffer to 240m in may 2017. But we recently figured out that the reduced dilation was degrading our estimates of  aerosols, as undetected clouds are considered as aerosols.  Due to this, the new version which runs since the2nd of February has once again a dilation of 480m.

Left, aerosol validation results with a dilation of 240m, right with a dilation of 480m. The new result brings a significant improvement (Merci à Bastien Rouquié pour ce résultat)

## Using NDVI with atmospherically corrected data

### NDVI

NDVI is by far the most commonly used vegetation index. NDVI was developed in the early seventies (Rouse 1973, Tucker 1979), and widely used with remote sensing in the nineties until now. It is computed from the surface reflectance in the red and near infra-red channels on each side of the red-edge.

$NDVI=\frac{\rho(NIR)-\rho(RED)}{\rho(NIR)+\rho(RED)}$

where $\rho(NIR)$ and $\rho(RED)$ are reflectances in the NIR and RED. Although several users still use top-of atmosphere reflectances (TOA), surface reflectances should be used to reduce sensitivity to variations of aerosol atmospheric content.

A time profile of surface reflectance from Sentinel2 satellite for the blue, green, red and NIR spectral bands for a summer crop in South East France. The observation under constant viewing angles minimizes directional effects.One can also notice that reflectance variations related to vegetation status are greater in the near infra-red, while the noise is usually lower. As a result, a vegetation index should rely more on the NIR than on the red.

I think NDVI is mainly used for the following reasons (but feel free to comment and add your reasons) :

• it has the large advantage of qualifying the vegetation status with only one dimension, instead of N dimensions if we consider the reflectances of each channel. Of course, by replacing N dimensions by only one, a lot of information is lost.
• it  enables to reduce the temporal noise due to directional effects. But with the Landsat, Sentinel-2 or Venµs satellites, which observe under constant viewing angles, the directional effects have been considerably reduced.

I therefore tend to tell students that if NDVI is convenient, it is not the only way to monitor vegetation.

## Users of THEIA Sentinel2 products are welcome in Toulouse, 13-14th June 2018

This is Toulouse in mid-June last year. Isn't that a nice place and time to gather the users of Sentinel-2 products delivered by Theia ?

CNES and THEIA are very happy to invite you to provide your feedback on the Sentinel-2 products we have been delivering for more than one year, thanks to the MUSCATE ground segment and the MAJA processor.

All users of MACCS/MAJA procesor and of THEIA products are welcome to tell us their findings, suggestions, and share experiences on methods, applications, and results.  We will also provide an update  about the processing perspectives, validation results, description of new versions, and you will have the opportunity to influence us on the related choices.

Please register and send your abstract to the workshop site. Here are the important dates to remember :

• abstract submission deadline : March the 8th.
• registration deadline : June the 3rd (we only have 100 seats, so please register quickly)
• workshop dates 13-14th June 2018

## [MUSCATE News] Production still on, but distribution stalled again

Update January 31st, 10h00 : Distribution was just restarted, a few hundreds of images will be added today, and meanwhile, data are processed in Near Real Time.

This January was a nightmare for MUSCATE. Following database issues to send data to the distribution server, our production system was stopped during the Christmas break and unstable the weeks after.

After understanding the issues, the MUSCATE team stopped the automatic sending of products, resumed the production, and started to update the production server manually. We were nearly back on track last Thursday, when the distribution server refuse to accept any new product. The explanation was found, a directory in the High Performance Storage System (a robot that handles tapes and disks) had 65535 files and could not accept a new one.  We need a little reorganisation of the folder structure to overcome that, and meanwhile, the distribution is stalled again.

Still, more than 60 000 L2A products are now available, and we have started distributing the snow cover products, in NRTWD  ("Near real time with delay"). We hope to be soon really in NRT.