Revised spectral bands for Sentinel-2A

The Sentinel-2 mission status document, edited by ESA, is a very interesting reading. On its last edition of 2017, ESA announced very discretely that the spectral bands of Sentinel-2 had been revised, following a review of the pre-flight measurements. Very few details are provided on the nature of the error contained in the previous version, and on the validation of the new ones. But still, a new version of the spectral response function is available here,, since the 19th of December 2017. The site provides an excel file with the spectral response functions.

All the visible and near infrared bands have changed a little, even if only three bands have significant changes, B1, B2 and B8: B2 equivalent wavelength changes by 4 nm, B1 by 1 nm, and B8 by 2 nm. The SWIR bands did not change.

Old and new versions of five VNIR S2A spectral bands, together with that of S2B.

Most users should not use bands B1 and B2, as they are affected by atmospheric effects. So I do not think much of you will have to change the coefficients in your methods. But for us, who take charge of the atmospheric correction, and heavily rely on B1 and B2, it probably has an effect, and we are changing our look-up tables to account for that. Stay tuned for the results.

Venµs mission status, 5 months after launch

Hereafter some news on the status of the Venµs mission.

Venµs was successfully launched from the Kourou space port on August 1st by a VEGA launcher:

 

https://vega.cnes.fr/en/live-vega-launch-venus-august-first-2017

 

First images were acquired by mid-August (see below for examples). The commissioning phase is still running. This phase consists in checking the whole system, including the satellite, the camera, the download of the images and data to the Kiruna receiving station, the ground processing chains, as well as the geometric and radiometric calibrations. All these components are in a good health and working well. However, given the very demanding requirements in terms of multitemporal registration, more work than anticipated is needed to fine tune the AOCS (Attitude and Orbital Control Subsystem) and the processing algorithms. In addition, the first part of the in-flight demonstration of the electric engine developed by RAFAEL (called IHET) will take place from mid-december to mid-january.

 

For these reasons, CNES and ISA plan to resume the systematic acquisitions of the scientific sites early 2018. Preparing the reference images for every site and checking the quality of time series will also take some weeks. We anticipate delivering the Level 1 (top of the atmosphere reflectances, orthorectified) products by april 2018, but all the data acquired from the beginning of systematic acquisitions will be processed and made available on the Theia web site:

http://www.theia-land.fr/en/products/venus

 

Level 2 data (top of the canopy reflectances) might be available slightly later since the method we use requires a time series of data.

You will find some examples of images following the links below :

 

https://presse.cnes.fr/en/france-israel-space-cooperation-venus-vegetation-monitoring-satellite-sends-back-first-images

and here:

 

http://www.cesbio.ups-tlse.fr/multitemp/?p=11215

http://www.cesbio.ups-tlse.fr/multitemp/?p=11096

http://www.cesbio.ups-tlse.fr/multitemp/?p=11344

 

The Moon is also acquired for calibration monitoring purposes:

http://www.cesbio.ups-tlse.fr/multitemp/?p=11344

 

We thank you for your patience. We are doing our best to provide you with quality products.

Happy New Year to you all

Our blog's audience in 2018

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A sixth year begins for the "Séries temporelles" blog, and as usual, it is an opportunity to review its audience, and to get a little self-satisfaction.

The blog is always receiving more visits. even if the annual growth rate is much lower than the previous years, but still 20%... French visitors constitute only 35% of visits. The United States rank second, followed by Morocco, which is probably an effect of CESBIO's long presence in Marrakesh. Then come France neighbouring countries.

 

2013 2014 2015 2016 2017
Number of visits 13985 22928 34723 47773 57692
Number of viewed pages 30922 46940 66947 89555 105846

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Canigou 3D

Lo Canigó és una magnòlia immensa
que en un rebrot del Pirineu se bada
- Jacint Verdaguer i Santaló

 

The Canigó is an immense magnolia
that blooms in an offshoot of the Pyrenees

 

3D view of the Canigou on 19-Dec-2017 (with a fancy tiltshift effect)

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MAJA Sentinel-2 L2A processor downloaded more than 200 times

Since spring 2017, we have made the MAJA cloud screening and atmospheric correction processor available for commercial use. A bit later, end of June, the Sen2agri software package, which includes MAJA older version (named MACCS) , was also released to the public. We did not expect a large success, as these two packages are quite heavy ones, do not work on laptops, and require a specific linux system powerful computers (Red Hat or CentOS).

Anyway, the MAJA processor has had quite a large success, even if, I guess, it is far from the success of Sen2cor, which is much easier to install and use, even if the performances are not the same. The figures below correspond nearly to one download per day.

 

Number of downloads of MAJA (stand alone version) 93
Number of downloads of MACCS (Sen2Agri version)i 116

 

To celebrate this fact, we just published a brand new MAJA detailed description.

A brand new MAJA ATBD

I have always wanted to provide an Algorithm Theoretical Basis Document related to MAJA, but never had time, because I always had more urgent things to do. Some papers had been published, allowing MAJA users to get a good idea or the methods we use, but the published articles did not cover all the features of MAJA.

 

But this time, due to a contractual engagement with ESA, it was the urgent thing to do. So, at last, after a few weeks of hard work, here it is.

 

If you have already read the papers from our team, you will recognize some text published quite a long time ago, but we updated all the text and added some parts which had not been explained yet in journal publications, and of course the new parts recently added to MAJA. This ATBD is now in line with version 2.0 of MAJA.

Using aerosol type from Copernicus Atmosphere in MAJA

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The main difficulty of the atmospheric correction comes from the determination of the aerosols optical properties: one has to know the optical properties of the aerosol type present in the atmosphere and determine their optical thickness. Using Sentinel-2 data to determine the aerosol type is very complicated, and our MAJA processor, used to generate Theia L2A products, only computes the aerosol optical thickness, while assuming a specific aerosol type.

 

The current operational version of the MAJA processor uses a constant aerosol type during the atmospheric correction, independently from the location and from the time of the year, thus affecting the quality of the atmospheric correction if the chosen aerosol type is not appropriate.

 

As an alternative, we tried to use the information from CAMS (Copernicus Atmosphere Monitoring Service), whichprovides forecasts of the Aerosol Optical Thickness (AOT, see figure below) of five different aerosol types: dust, black carbon, sea salt, sulfate and organic matter.

 

CAMS aerosol optical thickness (AOT) forecasts at 550 nm on 14 June 2016, 03:00 UTC: (top left) Dust, (top right) Sea Salt, (bottom left) Black Carbon, and (bottom right) Sulfate.

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Using multi-temporal high-resolution remote sensing in surface modeling

Version française par ici.

 

The land surface models simulate the water and energy fluxes between soil, land cover and atmosphere. Their scopes of application spread from numerical weather prevision to soil water modeling.

 

Energy and water budgets of the soil-plant continuum

 

However, these models are initially conceived to be applied on wide areas. Thus, they use low resolution cover parameters (>1km) derived from mid-resolution satellite observations (MODIS, VEGETATION). These parameters are mainly the Leaf Area Index (LAI), the vegetation type or the surface albedo. Yet the agricultural landscapes of Western Europe are characterized by a patchwork of plots smaller than one square kilometer. These plots have very different vegetation cycles, i.e. winter and summer crops, which could only be described at high resolution. The crop management practices like crop rotation or irrigation are also generally not taken into account.

 

The products of the Sentinel-2 space mission, with their high spatial and temporal resolution, could bring elements to fill in this missing information.

 
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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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