Building a global cropland mask, is not an easy task

Criticizing is easy, and doing is hard, especially when trying to create a global map of croplands. Some collegues from CESBIO have worked on that subject within the Sen2Agri project, and obtained good resuts, but only at the local or country scale. Finding a method that works everywhere must clearly be much harder.

These days, I have received a lot of emails, tweets and posts about a new cropland global product at 30 m resolution, edited by USGS. I have no doubt it was a serious work from a serious team, done with appropriate terrain data and methods, validation, and of course a tremendous data processing.

 

 

But there it is, I checked it over a lot of places that I know very well, and it seems to me that the cropland mask, at least in South West France, is clearly overestimated. Is it the same in tour region ? Here are some examples :

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Yesterday's snow cover area in the Pyrenees

Olivier pointed to me that ESA's ground segment, PEPS and MUSCATE were all in really good shape today... And the sky was clear yesterday at the time of the Sentinel-2A acquisition!

So I could download the Level-2A product from theia.cnes.fr, run our let-it-snow processor, start QGIS and here it is: the map of yesterday's snow cover area at 20 m resolution. If you know the region, you might notice that there is currently a big contrast in the snow cover extent between the French and the Spanish Pyrenees. This is due to the blocking of the moist air masses coming from the north.

Snow cover area on 22 Nov 2017. blue: snow, grey: no snow, white: cloud.

Stay tuned! Theia should start to distribute these Sentinel-2 snow products in near real time very soon.

MUSCATE news : 50000 L2A products from Sentinel-2A and 2B

Since it became operationnal in December last year, MUSCATE has produced 50 000 level 2A products from Sentinel-2A. Let's recall what has been processed so far :
  • For 550 tiles, we have processed all Sentinel-2A data acquired since December 2015.
  • For 100 tiles, mainly in South America, and in Italy, we have processed all Sentinel-2A data from December 2016. We are currently catching up the backlog for Italy, and later on, for South American sites.
  • For all these 650 tiles, we are producing all Sentinel-2 data (Sentinel-2A and Sentinel-2B) in near real time. I think THEIA is the only place where you can download Sentinel-2B L2A data so far. ESA has not started that production yet (nah, nah, nah :) )
  • For all these 650 tiles, we have processed all Sentinel-2B data since beginning of October 2017. We will soon catch-up with the Sentinel-2B data acquired from July 2017.

 

 

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Map of the 650 tiles currently processed in near real time (in red). The blue tiles will be added beginning of next year.

 

All these products are available from https://theia.cnes.fr

 

Let's recall that MUSCATE uses the MAJA L2A processor, which uses multi-temporal criteria to perform a high quality cloud detection and atmospheric correction. Despite the recent installation of version 2.4, MUSCATE still regularly suffers from instability as soon as CNES High Performance Computer is overloaded. The problem does not lie in MAJA, but in the information exchanges between all the components of MUSCATE which need to respect an accurate timing (sorry, I am not able to explain better).

 

The exploitation team just installed a new version of MUSCATE (v 2.4.16.p2 (!)), which is expected to increase stability. But that's the theory, let's see if it works in the coming days and if we are able to increase our production rate.

 

 

Evolution of the snow cover area in the Pyrenees from MODIS

The Cesbio contributes to the Pyrenees Climate Change Observatory (OPCC) through the analysis of the snow cover evolution using satellite imagery. We are working on three remote sensing products in the framework of the CLIM'PY project:

    1. Daily cloud-free maps of the snow cover area in the Pyrenees at 500 m resolution since 2000 from MODIS [1];
    2. Maps of the snow cover area in the Pyrenees at 20 m and 30 m resolution since 2013 from Sentinel-2 and Landsat-8 [2];
    3. Maps of the annual peak snow depth in the Bassiès-Vicdessos region at 4 m resolution since 2015 (i.e., one map per year) from Pléiades stereo imagery [3].

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Sentinel-2 mission close to start observing all lands every 5th day, really !

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Update : ESA is progressing fast. All lands overflown by Sentinel-2B were available in PEPS on November 12th, thanks to EDRS relay satellites.

The Sentinel-2 mission, made of two twin satellites S2A and S2B, has been stated "operational" since beginning of October, even if each satellite was only observing on one orbit out of two everywhere except in Europe and Africa. As a result, the 5 days revisit was only available in these two continents.  But in the new Sentinel-2 mission status report, ESA announced this very good piece of news :

Sentinel-2A and -2B are together acquiring Europe, Africa and Greenland with 5 days revisit. The rest of the World is revisited every 10 days jointly by the two satellites. Full systematic 5-day revisit everywhere will be reached once EDRS downlink becomes available operationally, assumed during December 2017 for both S2A and S2B.

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[MUSCATE News] Processing of Sentinel-2B L2A products begins

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ESA declared Sentinel-2B operational at the beginning of October, although preliminary data were already available. Since this morning, MUSCATE is producing and distributing Sentinel-2B Level 2A products using the MAJA processor (the L2A products are expressed in surface reflectance after atmospheric correction and are provided with a good quality cloud mask). The current production starts from the first of October 2017 and will go on in real time, and we will progressively add the Sentinel-2B products acquired since July 2017.

 

First S2B products available for download from https://theia.cnes.fr

 

As always, the data can be freely downloaded from https://theia.cnes.fr

 

Here is a little example of time series of iimages acquired over Baotou, China, alternatively by Sentinel-2A and Sentinel-2B, here again, the images look the same, except where something has clearly changed on the ground, in the east-west irrigarted valley in the image center.

Sentinel-2A Sentinel-2B Sentinel-2A

 

As MAJA processing is multi-temporal, its accuracy will benefit from the doubled repetitivity of acquisition, which should have an effect on our validation results. Using the production we did to check our  parameters, we have already checked that the reflectances provided by both sensors are quite close, and agree well with in situ measurements obtained with CNES surface reflectance measuring station in La Crau. The results are provided below.

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Snow cover in the High Mountain Asia on 13 May 1960

TIROS-1 weather satellite was launched by NASA on 01 April 1960. It took the first weather satellite picture on 02 April 1960 [1], and also the real first weather satellite picture on 01 April 1960 [2].
 
On 02 April 1960 it took what I believe is the first publicly available satellite picture of the snow cover in the Alps (picture 1 below). On 13 May 1960 it captured a stunning view of the snow cover over the High Mountain Asia, including the Himalayas, Hindu Kush, Pamir and Karakoram ranges. These pictures are shown in the TIROS-1 final report [3].


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Yellow skies look grey from above

You must have seen, in the press or social networks, images like these ones, showing yellow skies ( Loup de Bretagne said "Blade Runner skies"). Such a coloured sky was seen in the west of France, then later in England, and further East in the next days.

The Copernicus Atmosphere Monitoring Service, which keeps track of aerosols has also monitored these aerosols and tracked their provenance : is due to the combined presence of dust, ash from forest fires in Spain and Portugal, and humidity brought by the Ophelia cyclone. The IASI sensor on-board METOP satellites has also monitored the gases absorption due those wildfires.

 

So our question is: how such an event is handled by atmospheric correction software ?

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Venµs' moon

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Well, the audience of our blog is still steady increasing, there is no need to use explicit titles to get more connexions. And although I mainly use space to look down, I do not think the planet has a natural satellite. So why this title ?

The Venµs satellite actually showed us the moon, and not only to provide a nice title in this blog. Our Israeli colleagues from MBT really worked hard to obtain it, as a very good pointing accuracy is needed to image it from a quickly rotating satellite : the moon is far from here !

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