## [MUSCATE News] Retraitement des données Sentinel-2B acquises de Juillet à Octobre 2017

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MUSCATE est en grande forme ces jours-ci, grâce aux efforts de l'équipe de développement (CNES et CAP GEMINI), qui ont résolu de nombreux problèmes récemment. Le compteur des produits de niveau 2A de Sentinel-2 vient de dépasser 70 000, juste un mois après avoir passé 60 000. Si on fait la somme de tous les produits distribués par  THEIA, on arrive à plus de 99000. Theia distribue aussi des masques de neige sur les montagnes à partir de Sentinel-2, and des données Spot World Heritage (les anciennes données SPOT retraitées, ortho-rectifiées et disponibles gratuitement).

Cette grande forme nous permet d'augmenter les rythmes de production. Nous avons commencé à traiter les données Sentinel-2B acquises entre Juillet et Octobre 2017, car nous ne traitions S2B que depuis Novembre dernier. Mais comme MAJA est une méthode multi-temporelle, c'est un véritable retraitement que nous venons de lancer, en incluant à la fois S2A et S2B. La qualité des données S2A devrait elle aussi bénéficier de l'amélioration de la répétitivité des observations.

Ce retraitement va prendre quelques semaines. Il commence avec la France (ROM COM inclus), puis va s'étendre à nos voisins Européens. Puis viendra le tour du site sur le Maghreb, le reste des sites Africains, et enfin les autres sites répartis dans le monde.

Si vous avez que votre site soit traité de manière plus rapide, n'hésitez pas à demander ! (Bien sûr, cela ne s'applique qu'aux tuiles déjà présentes sur notre liste).

## [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)

## Improvement of high cloud detection in MAJA for Sentinel-2 images.

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The research to improve the performances of our MAJA atmospheric correction processor relies on a very small team within CESBIO, with two persons, Bastien Rouquié, who is working at improving aerosol retrievals, and myself, who spend most of the time in meetings, or writing blog posts, and sometimes doing both simultaneously . This is why improvements take time.

Atmospheric absorption : in blue, the surface reflectance of a vegetation pixel, as a function of wavelength. In red, the reflectance of the same pixel at the top of atmosphere. For a wavelength of 1.38 µm, water vapour totally absorbs the light that comes from the earth surface at sea level.

Anyway, I recently found some time to work on improving cloud masks above water. And these last days, i worked at improving the detection of high cloud using the cirrus band, which is available on Sentinel-2 as well as Landsat 8. As explained in this post, the "cirrus" band is locates in a strong absorption band of water vapour, strong enough to prevent photons from going from the sun to the satellite via the earth surface at sea level. As most of the water vapour lies in the low layers of the atmosphere, the clouds situated higher in the atmosphere have more chances to reflect light to the satellite. As a result, this channel allows us to detect the high clouds.

The detection method looks simple : just use a threshold on the cirrus band. Well that's not that easy !

## 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.

## [Muscate news] Distribution server operational again

MUSCATE distribution server is back to operations. Hundreds of products are currently being uploaded, which should take several hours.

Le serveur de distribution de MUSCATE est de nouveau opérationnel. Quelques heures seront toutefois nécessaires pour importer toutes les données produites pendant la semaine écoulée.

## [MUSCATE news] Distribution server in maintenance

New update: Muscate distribution server is back but you should use the following address until Monday: https://theia.cnes.fr/atdistrib/rocket/#/home . New products will be uploaded starting from Monday too. And since the week-end is there, it is not compulsary to downloard our L2A images until then (even if you can...)

Update : the server will also be down of Friday . Sorry for that

In order to solve the issue described in this post, MUSCATE distribution server is in maintenance. The distribution of new products should resume  tomorrow (Wednesday) or Thursday. Meanwhile, the production is going on. Sorry for the inconvenience.

Le serveur de distribution de MUSCATE est en maintenance pour résoudre le problème décrit dans cet article. La distribution de nouveaux produits devrait reprendre demain (mercredi) ou jeudi. Pendant les travaux, la production continue. Veuillez nous excuser pour ces perturbations.

## 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.