And now, LANDSAT 8 2014

A partir de maintenant, le pôle THEIA mettra en ligne tous les mois un lot de données LANDSAT 8 supplémentaire, récemment acquises au dessus de la France. Le dernier lot publié va jusqu'au 31 mai 2014. Les données sont toujours à la même adresse : http://spirit.cnes.fr/resto/Landsat/

Nous vous conseillons toujours la lecture de la description de leur traitement, du guide d'utilisation du serveur de distribution, et de la méthode pour télécharger des lots de données d'un seul coup.

 

From now on, THEIA will release each month a new bunch of LANDSAT 8 products recently acquired over France. The most recent date is now the 31st of May 2014. The data can be downloaded from : http://spirit.cnes.fr/resto/Landsat/.

We still advise you also to read the processing description. the short user's guide for the distribution server, and a manual to download a lot of data at once.

LANDSAT 5 et 7 data over France are on line !

C'est fait, les données Landsat 5 et 7 au niveau 2A sont en ligne sur le serveur de THEIA. Elles sont accessibles depuis cette adresse http://spirit.cnes.fr/resto/Landsat/

Nous vous conseillons aussi la lecture du guide d'utilisation du serveur de distribution, et la description de leur traitement.

 

The LANDSAT 5 and 7 data at level 2A are available on THEIA's server. You may access them from http://spirit.cnes.fr/resto/Landsat/.

We advise you also to read the short user's guide for the distribution server, as well as the processing description.

Phased orbits, how do they work ?

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As we are working to set a new Take5 experiment with SPOT5, here are some explanations of how it is possible to change the repeat cycle of a satellite from 26 days to 5 days, by just changing the satellite altitude by a couple of kilometres. There is nothing complicated behind that, just some simple arithmetic.

A phased orbit is an orbit for which the satellite repeats the same trajectory periodically. From its orbit at an altitude of 822 km, SPOT5, like its predecessors, has a cycle of 26 days. Every 26 days, it overflies the same places on earth. In 26 days, SPOT5 makes 369 revolutions around the earth. In 24 hours, a SPOT satellite runs through 369/26=14.19 orbits. Lowering its altitude by 2 km, the satellite slows a little, but the length of the circle it has to run along is reduced. It takes a little less time to make a revolution around the earth. The satellite does exactly 14.2 orbits per day.

 

Here are some of the orbits of SPOT4 (Take5), with some of the sites observed in France and North Africa during the experiment. The satellite started with the Cyan track, then the green one on the day after, then the yellow one on the next day and so on. 5 days later, it came back to the cyan orbit. You may see that it was possible to acquire a site on on the green track from the adjacent one on the cyan track.

 

14.2 orbits per days, is equivalent to 71 orbits in 5 days. After 71 orbits and 5 days exactly  SPOT4 was always at the same place during the Take5 experiment, and its cycled was changed from 26 to 5 days.

 

I have been also asked how the initial 26 days repeat cycle of SPOT5 was defined. The CNES engineers who designed it wanted to make it possible to observe each point on the earth from the vertical. As the SPOT satellites had a field of view of 116 km using both instruments, with a 26 days repeat cycle we had 116x26x14.19 = 43000km, just a little more than earth equator length. However, it was quickly seen that users did not ask for exactly vertical images and that the instruments were programmed mostly independently looking in different directions. However, the 26 days cycle was kept for all the SPOT satellites just as the High Speed Trains rail separation is related to the width of the hindquarters of a horse.

Finally, nothing would prevent from using the SPOT satellites from a 5 days repeat cycle orbit, which would not really change the ability to use the images how they are used now, but would allow new possibilities thanks to the possibility to observe users from constant viewing angles.

 

It is a little funny to observe that SPOT6 and SPOT7 do not use the initial SPOT orbit, and only fly at an altitude of 694 km but still with a 26 days phased orbit, this time obtained with 379/26=14.58 orbits per day. However, the justification cannot be the field of view, as this field of view is only 60 km.  But just by rising the orbit by a few kilometers, a 5 days orbit could be obtained

 

 

 

LANDSAT 5 & 7 acquired above France since 2009 soon released by THEIA

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As for LANDSAT 8 a few weeks ago, we just produced the level 2A products for the LANDSAT 5 et LANDSAT 7 data acquired above France from 2009 to 2011. This data set will be released in a few days, when its transfer to the distribution server has ended. The MUSCATE team took charge of the processing for the THEIA Land data center, using CNES computing center. The data will be available on the following site :

http://spirit.cnes.fr/resto/Landsat/

Example of a Level 2A product from LANDSAT 5 over the Atlantic coast of France. The clouds are circled in green, the water mask in blue, and the snow in pink. Sometimes, the water turbidity provides a signal similar to snow in the infra-red, which turns the now flag on...

The processing methods and the data format are similar to the LANDSAT 8 data set described here. However there are also a few differences which are detailed below :

 

Starting point.

The starting point is not the same for LANDSAT 5 and LANDSAT 7 :

  • For LANDSAT 7, as for LANDSAT 8, we start from Level 1T products provided by USGS. These products have a huge defect, with black stripes appearing away from the center axis of the image. These stripes are due to the breakdown of a mirror in 2003. The origin of this defect is described here. In our case, we decided to use only the central part of the images, doing a slight interpolation when the stripes are thin, and removing the data when the lack stripes are too large.
  • LANDSAT 5 data acquired above France are not yet available at USGS. ESA owns these data and agreed to provide them  (Thanks to Bianca Hoersh and Riccardo Biasutti from ESA, and to the SERCO company who processed the data). As a result, this data set is a unique data set, only available online here and nowhere else ! These data are provided at level 1G, for which the data have not yet been ortho-rectified.  We had to ortho-rectify them at Theia, using CNES's SIGMA tool, as for SPOT4 (Take5).
  • Having a different approach for both sensors has a drawback. The grounc control point data base used at USGS seems to have some errors in France, and for instance, the location errors near Toulouse have a bias of about one pixel southward. It is not the case for the LANDSAT5 data ortho-rectified by THEIA, and therefore, one may observe registration errors in a time series involving LANDSAT 5 and LANDSAT 7 images. ESA's data also have some defects, which are presented at the end of this post.
Resampling to Lambert'93 projection

Level 1T data are provided with the UTM projection. This projections uses three different zones over France, for which the registration of data is not direct. We decided to resample the data on a Lambert'93 projection, which is the official French projection. Of course, the LANDSAT5 have been directly projected in Lambert 93.

Tiling of products

We chose to tile the data in 110*110 km tile s spaced with a 100 km interval, as it will be done for Sentinel-2. The (1,1) tile is in the SouthWest corner of France. The tile of Toulouse is the 5th to the West, and the 2nd to the North. It is named D0005H0002 (D for "droite", H for "Haut"). For Corsica, a different tiling made of 2 tiles was defined.

 

For each tile, we provide the whole set of dates for which a LANDSAT 5 or 7 image intersects the tile. A few date may be missing, for several reasons, in general related to the cloud cover :

  • The image was not acquired by LANDSAT 5 or 7 (when a 100% cloud cover is forecast, the image is not acquired).
  • The image was acquired but not processed to L1T by LANDSAT7 at USGS, or to L1C at CNES, because the cloud cover prevented from using a sufficient number of ground control points
  • The Level 2A processing rejects images with more than 90% of cloud cover.

 

Level 2A processing (atmospheric correction and cloud screening)

First of all, we would like to outline that our processor does not process the themal bands of LANDSAT

 

For the visible, near and short wave infrared bands, we use the same method as for SPOT4(Take5). It involves also the MACCS processor, developed and maintained by Mireille Huc at CESBIO. It is based on multi-temporal methods for cloud screening, cloud shadow detection, water detection as well as for the estimation of the aerosol optical thickness.

 

However, thanks to LANDSAT spectral bands, our processing was enriched compared to SPOT4 (Take5). Thanks to the blue band, we have an additional criterion to detect the aerosols, thanks to the quasi constant relationship between the surface reflectances in the blue and in the red above vegetation. The precision gain due to this criterion compensates for the precision loss due the lower repetitivity of  LANDSAT images. Finally, as there is no 1.38 µm band on LANDSAT 5 and 7, the detection of high clouds is much less easy than for LANDSAT 8.

 

Images of one of the Atlantic Coast tiles, coming from different LANDSAT Paths (left and middle, tracks 201 and 200). The viewing angles are slightly different as the left image was observed from the West and the rmiddle image from the East. On the right, a Landsat7 image from track 201 reduced to its central part.

To increase repetitivity of observation which is essential in our multi-temporal method, we decided to use time series that merge LANDSAT 5 and LANDSAT 7 data as well as LANDSAT 5 data coming from adjacent tracks. As these data are not observed under the same viewing angle (+/- 7 degrees), but the angle difference is small enough to increase precision on the overlap zones, even if it may cause the appearance of artefacts in the AOT images.

 

Data Format

For LANDSAT 5 and 7, we used the same format as for SPOT4 (Take5).

 

Known issues :

Here is a little list of known defects for THEIA's LANDSAT 5 and 7 L2A products :

Example of LANDSATV5 "afterglow" issue near a large cloud. This electronic issue takes the appearance of whiter stripes above vegetation.

- reference data for ortho-rectification at USGS may be biased by more than 30 m (38 m in Toulouse). The Landsat 8 data could be misregistered with the LANDSAT 5 data ortho-rectified at CNES using a national geographical reference.

- LANDSAT 5 TM instrument electronics have an "afterglow" issue, that causes the appearance of whiter stripes perpendicularly to the satellite track near very bright zones such as a large cloud.

- ESA's LANDSAT 5 products have some random bright spots that appear as colored spots in color composites.

Bright color spots observed on some ESA LANDSAT 5 images.

- in LANDSAT products, the "nodata" value that tells if a pixel is outside the image is 0, which is also a value observed within the image. Sometimes pixels may be identified as nodata when the are in fact within the image. It happens mainly over sea, where the medium infrared reflectance is often equal to zero. In this case, all the bands have the nodata value which, in our products is -10 000, to avoid the same difficulties for subsequent users.

SPOT4 (Take5) communications at the Sentinel-2 Symposium

The second "Sentinel-2 for science" symposium , organised by ESA, took place in italy late may 2014. More than 400 future Sentinel-2 users participated, which is a record for a conference organised by ESA at ESA premises. Compared to the first Sentinel-2 users workshop, it turns out that most of the talks were based on time series of images, while this proportion was less than a third for the first users symposium (other talks were about spectral indexes, mono date model inversions, which is good science but is not specifically tailored for Sentinel-2). This shows that the Sentinel-2 users community state of preparation did a lot of progress during the two last years.

 

To this respect, it seems that the SPOT4(Take5) experiment has helped a lot, as at least 15 of the 55 talks (and a lot of posters) of the symposium were largely based on the data set. That was exactly the purpose of the experiment and I am quite please to see it succeeded. The data are still available there, and there are still a lot of things to do.

 

Here are the links to the 15 talks that use SPOT4 (Take5) data (I may have forgotten one of two, if so please tell me ! I have not found the links to the posters, if someone found them, please tell me !).  You may also access the whole program here (some talks, although not based on SPOT4 (Take5), were also very stimulating ;-) )

 

Ground Segment


MUSCATE : An Operational Tool for Atmospheric Corrections And Monthly Composites Sentinel-2

Marc Leroy1, Olivier Hagolle2, Mireille Huc2, Mohammed Kadiri2, Gérard Dedieu2, Joëlle Donadieu1, Philippe Pacholczyk1, Céline L'Helguen1, Selma Cherchali1

1: CNES, France; 2: CESBIO


Pre-processing


Lessons learned from the SPOT4 (Take5) experiment : simulations of Sentinel-2 time series on 45 large sites

Olivier Hagolle1,3, Mireille Huc1,2, Mohamed Kadiri1,2, Dominique Clesse4, Sylvia Sylvander3, Marc Leroy3, Martin Claverie5, Gérard Dedieu1,3

1: CESBIO Umr 5126 CNRS-CNES-IRD-UPS, Toulouse, France; 2: CNRS,France; 3: CNES, France; 4: CAP GEMINI, France; 5: NASA/GSFC, USA

Eric Vermote1, Martin Claverie1,2, Jeffrey Masek3, Inbal Becker-Reshef2, Chris Justice2

1: NASA/GSFC Code 619; 2: University of Maryland, Dept of Geographical Sciences; 3: NASA/GSFC Code 618


Restoration of Missing Data due to Clouds on Optical Satellite Imagery Using Neural Networks

Nataliia Kussul, Sergii Skakun, Ruslan Basarab

Space Research Institute NASU-SSAU, Ukraine


Agriculture


Agronomy and hydrology with Sentinel-2 type time series: Towards spatial characterization of crop productivity and its impacts on water and nutrient cycle at the catchment scale

Sylvain Ferrant1,2, Simon Gascoin2,3, Amanda Veloso2, Martin Claverie4, Gérard Dedieu1,2, Valerie Demarez2,5, Eric Ceschia2,5, Patrick Durand6, Jean-luc Probst3,7, Vincent Bustillo2,5

1: CNES, France; 2: CESBIO, France; 3: CNRS, France; 4: University of Maryland; 5: University of Toulouse; 6: INRA, France; 7: ECOLAB, France

Based on Formosat-2 rather than SPOT4 (Take5), but these data are similar and produced with the same methods.


Crop mapping in complex landscape by multi-source data mining and remote sensing for food security

Elodie Vintrou1, Valentine Lebourgeois2, Agnès Bégué2, Dino Ienco3, Maguelonne Teisseire3, Pierre Todoroff1, Fidiniaina Ramahandry Andriandrahona4

1: CIRAD UR AIDA, Station Ligne Paradis, 7 chemin de l’Irat, 97410 Saint Pierre, La Réunion; 2: CIRAD UMR TETIS, Maison de la Télédétection, 500 rue J.F. Breton, Montpellier, France; 3: IRSTEA UMR TETIS, Maison de la Télédétection, 500 rue J.F. Breton, Montpellier, France; 4: FOFIFA, Station Régionale de Recherche FOFIFA Tsivatrinikamo ANTSIRABE 110, Madagascar


Sentinel-2 Agriculture project: Preparing Sentinel-2 exploitation for agriculture monitoring

Defourny Pierre1, Bontemps Sophie1, Cara Cosmin4, Dedieu Gérard2, Guzzonato Eric3, Hagolle Olivier2, Inglada Jordi2, Rabaute Thierry3, Savinaud Mickael3, Sepulcre Guadalupe1, Valero Silvia2, Koetz Benjamin5

1: UCLouvain, Belgium; 2: CESBIO, France; 3: CS-Systèmes d’Information, France; 4: CS-Systèmes d’Information, Romania; 5: ESA, ESRIN, Italy


Crop Identification and acreage estimate using a combination of Spot4-Take5 & Landsat 8.  A preparatory study for Sentinel 2

N. Knox1,2, L.T. Tsoeleng1, C. Adjorlolo1,2, T. Newby3

1: South African National Space Agency (SANSA), South Africa; 2: University of KwaZulu-Natal (UKZN), South Africa; 3: National Earth Observation and Space Secretariat (NEOSS), c/o SIIU - CSIR, South Africa.


Multisource EO Data for the optimal agricultural drainage water management in semi-arid area of Doukkala (Western MOROCCO): Potential of Sentinel-2 Type Observation

Kamal Labbassi1, Nadia Akdim1, Silvia Maria Alfieri2,3, Massimo Menenti2

1: Chouaib Doukkaly University, Morocco; 2: Delft University of Technology, Netherlands; 3: Institute for Mediterranean Agricultural and Forest Systems, Italy


Forests


Potential of Sentinel 2 constellation to provide near real time forest disturbance mapping over cloudy areas in Gabon

Christophe Sannier, Louis-Vincent Fichet

SIRS, France


Assessing Forest Degradation from Selective Logging using Time Series of Fine Spatial Resolution Imagery in Republic of Congo

Astrid Verhegghen, Baudouin Desclée, Hugh Eva, Frédéric Achard

Joint Research Centre of the European Commission, Italy


Potential benefits that Sentinel-2 data could bring to characterise and monitor forestry, simulated through SPOT 4 Take5 data

Colette Meyer1, Hervé Yesou1, Stephen Clandillon1, Henri Giraud1, Jérôme Maxant1, Paul de Fraipont1, Arnaud Selle2

1: SERTIT, France; 2: CNES, France


 

Coastal and inland waters


Mapping estuarine turbidity using high and medium resolution time series imagery Virginie Lafon1, Arthur Robinet1, Tatiana Donnay2, David Doxaran2, Bertrand Lubac3, Eric Maneux1, Aldo Sottolichio3, Olivier Hagolle4, Alexandra Coynel3

1: GEO-Transfert, ADERA, Université de Bordeaux, France; 2: Laboratoire d'Océanographie de Villefranche, UMR 7093 - CNRS / UPMC, France; 3: UMR EPOC, Université de Bordeaux-CNRS, France; 4: CESBIO, CNRS,UPS, CNES, IRD, France


CoastColour Spot 4 Take 5

Carsten Brockmann1, Ruescas Ana1, Pinnock Simon2

1: Brockmann Consult GmbH, Germany; 2: ESA ESRIN, Italy


Sentinel-2 Time Series for GlobWetland II to map Threats in Wetlands

Kathrin Weise1, Marc Paganini2, Max Tobaschus1,3, Martin Faber1,3

1: Jena-Optronik GmbH, Germany; 2: European Space Agency, Italy; 3: Friedrich Schiller University Jena, Germnay

SPOT4 (Take5) surface reflectance validation using CNES ROSAS station in la Crau.

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More than 10 years ago, on the Crau plain, in Provence, CNES set up an automatic calibration station to measure the atmospheric optical properties and the surface reflectances. This station, named ROSAS (RObotic Station for Atmosphere and Surface), is at the top of a 10 meter mast, and is equipped with a CIMEL instrument similar to the ones of the AERONET network that are used to characterize the atmospheric aerosols. But this one has been modified to observe also the ground. The initial objective of this station was to check the absolute calibration of optical remote sensing instruments with a high resolution (because the site uniformity is not sufficient for satellites with a kilometric resolution). But this station proves also useful to validate the surface reflectances from satellite level 2A products.

 

This work was done by some CNES colleagues, Vincent Lonjou, Sébastien Marcq et Aimé Meygret, using the level 2A products obtained from SPOT4 (Take5) experiment.

The ROSAS station needs 90 minutes to fully characterize the downward radiance and thus the atmosphere, and the upward radiance. The ratio of both measurements enable to compute the surface reflectance. However, the process is a little more complex than described here, as the surface around the mast is not perfectly uniform and the reflectances are affected by directional effects. A bidirectional model is therefore fitted to the measurements, and this model is then used to predict the reflectances measured by the satellite.

B2

The ROSAS instrument, during the SPOT4 (Take5) experiment, was equipped with 10 spectral bands described in the table below. The instrument is now being modified in view of Sentinel-2 and Venµs launches, to accommodate new spectral bands, in the near infra-red mainly, where the sampling of the spectrum was not sufficient.

Band λ (nm), detector
1 1020Si
2 1600 InGaAs
3 870 Si
4 670 Si
5 440 Si
6 550 Si
7 1020 InGaAs
8 937 Si
9 380 Si
10 740 Si

B3 (clear symbols for SPOT4, dark symbols for ROSAS)

 

B4 (clear symbols for SPOT4, datk symbols for ROSAS)

The agreement of ROSAS and SPOT4(Take5) surface reflectance measurement is excellent, in all band but near-infrared : better than 5% in the green (B1), red (B2) and SWIR (B4) channels, and 7-8% in the NIR (B3). The differences observed in the NIR are being investigated, but could be linked to the spectral interpolation, as SPOT4 B3 band is quite far from ROSAS spectral bands.

In the SWIR, the greater variations of surface reflectances with time may be noticed, with large reflectance drops after rains. The SWIR band is very sensitive to the soil moisture, at least when the vegetation cover is sparse, which is the case at La Crau. In the other bands, these variations are much less visible, and what should be noticed is the great stability of surface reflectances with time, thanks to the acquisitions with constant viewing angles and also to the quality of atmospheric correction...

 

 

A poster was shown by Aimé Meygret at the "Sentinel-2 for science" symposium in Frascati in may 2014.

 

 

 

Level 2A LANDSAT data over France released by THEIA

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It is our great pleasure to announce that the LANDSAT 8 level 2A data produced by THEIA are available at the following address.

http://theia.cnes.fr/

 

The available data are all the data acquired by LANDSAT over France, for which a sufficient number of cloud free pixels were available. They were processed to Level 2A : they are expressed as surface reflectance after atmospheric correction, and are provided with a cloud mask. The way we produced them is explained here for LANDSAT 8 and here for LANDSAT 5 and 7.

The distribution server was developed by my CNES colleague Jérôme Gaspéri, helped by Rémi Mourembles from CAP Gemini ; it has a very simple but very modern interface, with only one simple field to formulate requests, which may be provided as sentences in day to day language. The tool indeed makes a semantic analysis of your requests. And it is meant to work as well on your computer, tablet or phone (but you should think before downloading a whole LANDSAT product on a smartphone).

 

Example of requests :

1) Date and location
LANDSAT7 images on Biarritz between january and june 2009
LANDSAT8 images on Toulouse acquired in may 2013
2) Research on land cover characteristics :
Herbaceous area on Jersey in 2013
Images with forest in October 2013
Images without forest in October 2013
3) Or any combination :
Images with cultivated area and forest on Paris between March and August 2010
Cultivated area on Bordeaux in August 2013
4) Telegraphic style
LANDSAT8 July 2013
Arcachon LANDSAT5

 

To select the geographic extent, you could also zoom on the map to define the region of interest fom the corners of the displayed region.

 

Finally, to download the product, you need first to create an account, by clicking on the orange icon, and then you need to identify yourself. Every image can be downloaded by clicking on the download button or directly using its URL defined from the product name. I have to write an automatic download script, but you may already use the very convenient DownThemAll Firefox plugin. To use it, you will have first to login, then to ask Downthemall to download all the URLs thant end with "$download". (HowTo provided here)

 

The publication of these data is the result of years of work, at CESBIO and CNES, although their production takes less than 2 weeks. It is also the first cersion of this processing. Positive comments are welcome, as well as negative, they will be useful to enhance the service, before we start processing Sentinel-2, which should be launched next year.

 

Finally, we would like to thank our NASA and USGS colleagues who distribute the input data with no restriction, which allows THEIA to deliver fully open data. Please do not forget to tell us about what you did with the data, it is very important to elp us justify our funding requests.

 

Completion of the processing of LANDSAT 8 Level 2A products taken above France in 2013.

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That was fast ! The processing of all the LANDSAT 8 images taken above France in 2013 took less than 15 days. The first LANDSAT 8 images were taken in April 2013. The MUSCATE team processed the data for the THEIA land data center, using CNES computing center.

 

A few more days will be necessary to upload the data on the THEIA website and to check that the data are correct. Finally, the longest part in the processing is the downloading of the input Level 1T products from USGS earthexplorer website (equivalent to the Level 1C in THEIA's nomenclature).

 

The Level 2A data quality is quite good, as may be seen on the browse products on the right, as shown by images on the right, which come from the times series obtained on the tile of Paris. As usual on this blog, the clouds are circled in green, the shadows in black, the snow in pink and the water in blue. A few clouds are sometimes missed by our multi-temporal method, when the repetitivity of cloud free acquisition is too low, as in the image on the right which was acquired during a cloudy spring. The following images in the time series are not affected by this kind of defect.

 

This paper aims at describing the main steps of the processing.

 

Starting point : Level 1T

We download the input data from the earthexplorer website, using an enhanced version of the script described here. These products are ortho-rectified by USGS, using a global data base of ground control points.

 

The location requirement for LANDSAT 8 is 50 m, which seems to be met by the L1T products. We found location errors around 1.5 pixels near Toulouse, but most regions seem to have better performances. USGS confirmed a 38m bias Southward near Toulouse and will try to correct them.  Our processing does not correct for these small errors, and the next version of the USGS LANDSAT 8 processing only wil lcorrect for this bias.

 

Regarding LANDSAT 8 absolute radiometric calibration, we use the coefficient values recommended by LANDSAT 8 and provided with the L1T products.

 

Resampling to Lambert'93 projection


Level 1T data are provided with the UTM projection. This projections uses three different zones over France, for which the registration of data is not direct. We decided to resample the data on a Lambert'93 projection, which is the official French projection.

Tiling of products

We chose to tile the data in 110*110 km tiles spaced with a 100 km interval, as it will be done for Sentinel-2. The (1,1) tile is in the SouthWest corner of France. The tile of Toulouse is the 5th to the West, and the 2nd to the North. It is named D0005H0002 (D for "droite", H for "Haut")

 

For Corsica, a different tiling made of 2 tiles was defined.

 

For each tile, we provide the whole set of dates for which a LANDSAT 8 image intersects the tile. A few date may be missing, for several reasons, in general related to the cloud cover :

  • The image was not acquired by LANDSAT 8 (when a 100% cloud cover is forecast, the image is not acquired).
  • The image was acquired but not processed to level 1T by LANDSAT8, because the cloud cover prevented from using a sufficient number of ground control points
  • The Level 2A processing rejects images with more than 90% of cloud cover.

 

Level 2A processing (atmospheric correction and cloud screening)

First of all, we would like to outline that our processor does not process the themal bands of LANDSAT 8.

For the visible, near and short wave infrared bands, we use the same method as for SPOT4(Take5). It involves also the MACCS processor, developed and maintained by Mireille Huc at CESBIO. It is based on multi-temporal methods for cloud screening, cloud shadow detection, water detection as well as for the estimation of the aerosol optical thickness.

 

However, thanks to LANDSAT 8 spectral bands, our processing was enriched compared to SPOT4 (Take5) : LANDSAT8's 1.38µm band enables an enhanced detection of high and thin clouds. And thanks to the blue band, we have an additional criterion to detect the aerosols, thanks to the quasi constant relationship between the surface reflectances in the blue and in the red above vegetation. The precision gain due to this criterion compensates for the precision loss due the lower repetitivity of  LANDSAT8 images.

Level 2A images from Paris's tile, from 3 different LANDSAT 8 tracks (From left to right, tracks 200, 199, 198). The viewing angle differs as the image is from the west on the left image, at nadir in the center and from the east for the right image.

 

To enhance the cloud screening accuracy, we decided to use the data from adjacent satellite tracks within the same time series. These data are not acquired under exactly the same angle (+/- 7 degrees), which is the assumed by the multi-temporal method, but the difference is small enough to allow a large accuracy gain due to the enhanced repetitivity. However, because of this approximation, a few artefacts may be observed.

 

For a greater enhancement, we might also use LANDSAT 7 and LANDSAT 8 data in the same time series, but we will implement that later on...

 

Data Format

For LANDSAT 8, we used the same format as for SPOT4 (Take5), excepted a few details, that I will describe soon...

 

 

 

Express your needs concerning agriculture monitoring using Sentinel-2 time series

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As you may know, we have been selected for ESA's project "Sentinel-2 Agriculture".  Among the tasks we must fulfill, we have to ask the users about their needs concerning the use of Sentinel-2 time series to monitor agriculture, and of course we need to write a synthesis.

 

ESA had already distributed a questionnaire at the S2 symposium in 2012, which was used as a basis to define the Sen2Agri project. My revered colleague (and boss) Gérard Dedieu, just cooked a new detailed survey form. If you are a potential user of remote sensed images for agriculture monitoring,  you are very welcome to fill this survey.

 

Although the baseline of SenAgri products was already defined in the call for tender, your answers will be very useful to detail the product requirements, and to forward your needs to ESA and other space agencies, and to define the next versions of our products.