Retour au plan A pour Theia-Muscate

Depuis deux mois, nous distribuons les données Sentinel-2 de niveau 2A sur la France sur le centre de traitement MUSCATE. Les données sont produites par le CNES, pour le compte de THEIA et disponibles à l'adresse ci-dessous :

 

https://theia.cnes.fr/atdistrib/rocket

 

Mais ces données étaient jusqu'ici produites selon le plan B : sur une plate-forme de test, avec une ancienne version des chaînes, puis transportées à la main sur le serveur de distribution. Mais il existe bien sûr un plan A  : production opérationnelle des données, sur la plate forme opérationnelle, avec la chaîne à jour. Le Plan A avait été suspendu, car le système MUSCATE était soupçonné d'avoir fait planter, au cœur du mois d’août le centre informatique du CNES en écroulant ses performances.  MUSCATE a été complètement disculpé après 7 semaines de tests. Le plan A a donc été activé, qualifié, et TATATA :

La production a démarré mardi soir (22 novembre) !

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Sentinel-2 to monitor forest fires in Siberia?

At the beginning of summer, a colleague in Igarka (Maxime Deschuyteneer ?) informed me on 20th of July that a forest fire up to the city was responsible, according to him, of “a small greenhouse effect that make you cough”…Indeed, forest fires are recurring problems in Central Siberia, mainly during June and July because of a sharp increase of temperatures. These fires have widely increased last years and the year 2016 would be the most “blazed” of history since, according to GreenPeace Russia, 3.5 million ha of forests have been burnt1, as big as seven French departments! On 24th September, NASA has also published an Aqua MODIS scene from 18th September 2016 showing huge plumes moving towards North East of Russia as well as zones (in red) where the satellite has detected unusual warm temperatures associated with fire2. The extent of MODIS image on the map of concentrations of aerosols allows presenting the scale of the phenomenon.

 

(at the top)- NASA’s Aqua satellite scene (MODIS) showing huge plumes2; (at the bottom) – Map of concentration of aerosols2


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Sentinel-2 captures the coastal ground uplift after Kaikoura earthquake in New Zealand

On Monday Nov 14 New Zealand was hit by an earthquake of magnitude 7.8. The epicenter was located near Kaikoura on the east coast of the South Island.

 

Yesterday, the NZ Herald published aerial photographs showing tectonic uplift of the seabed of between 2 and 2.5 metres north of Kaikoura [1]. These photos were taken by @TonkinTaylor who posted them on Twitter.

 

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Radiometric quantities : irradiance, radiance, reflectance

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Beware, this document contains equations

Radiometric quantities are numerous and may seem rather complex at first sight. Here is a little guide of the various quantities you might stumble upon when using optical remote sensing data. It might be a little boring, it is full-up with integral formulas, but well, to really understand what images mean, it might be useful. Come on, let's go, and cheers !

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Monthly cloud free syntheses merging Sentinel-2 and Landsat 8

To compute a cloud free synthesis of surface reflectances every month, a good repetitivity of observations is necessary. The weighted average method we developed at CESBIO, and which will be part of ESA's sen2agri system was coded by Cosmin Udroiu at CS Romania. It was meant to work with both Sentinel-2 sensors and an observation every fifth day. As we are still waiting for the launch of Sentinel-2B, the monthly syntheses obtained with Sentinel-2A alone really lack cloud free data.

 

On the left, the Sentinel-2A monthly synthesis, above Odessa (Ukraine) in May, and on the right its flag, with, in black, the areas flagged as cloud or cloud shadow. When a pixel is flagged as cloud or cloud shadow, the monthly synthesis provides the minimum blue reflectance, which tends to avoid clouds (if possible), but often selects cloud shadows.

 

Fortunately, the Sen2agri L3A processor is designed to work with LANDSAT 8 too, as both satellites have similar spectral bands, and as the MACCS atmospheric correction used to produce the L2A input products works for both sensors. Of course LANDSAT 8 geometric resolution is not that of Sentinel-2, so to avoid degrading Sentinel-2 imagery when LANDSAT8 data are available, we give Landsat 8 a very low weight in the weighted average. As a result, Landsat is really taken into account only when no cloud free Sentinel-2 was available during the synthesis period.

 

Same result as above, but including LANDSAT 8 data. A cloud free date at least is now found for every pixel. The water mask obtained from Level 2A product is a little wrong on the Landsat 8 image due to the presence of turbid waters and thin clouds. A solution for this problem will be implemented in next MACCS L2A version. Note that the monthly synthesis of both Sentinel-2 and LANDSAT-8 leaves nearly no visible artifacts on the lands.


For a better comparison of both versions, here is a little animation of composites with and without Landsat 8.

The Sen2Agri system is still in validation phase and should be released as open source next May, 6 months from now. The L3A synthesis processor will be also implemented within Theia and monthly L3A products will be distributed by Theia as it is already the case for L2A products.