The cloud detection : how it works.

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Clouds are white, bright, rather high in the sky. Their temperature is generally lower than that of the surface. They move and change appearance, and they cast shadows on the ground.

All these properties can be used to automatically detect clouds.

 

Standard detection

The basic technique consists in thresholding the image of a spectral band in the short wavelength range (preferably a blue band). Pixels whose reflectance is above the threshold are declared cloudy. This method is not very subtle and often does not detect thin clouds, it also makes many false detections. We can also check that the cloud is white, but the contribution of this verification is not really effective, because thin clouds are not perfectly white, while many bright pixels are white, in cities for example.

 

Multi-temporal detection

The clouds detected by the multi-temporal methodon this FORMOSAT-2 image are outlined by white contours. Note that some agricultural plots are brighter than some clouds, with nearly no confusion. Click on the image to view animation

A multi-temporal detection may be applied when time series of satellite images are available, if they are acquired with a roughly constant viewing angle, as in the case of SPOT4 (Take5), Venμs, LANDSAT, and Sentinel-2.

Usually, reflectances of land surfaces change slowly, but when a cloud appears, the reflectance increases sharply. So, by comparing the processed image with a previous image, the pixels for which the reflectance in the blue increased significantly can be classified as clouds, provided the detected pixels have a whiter spectrum than in the previous image. This method greatly improves the discrimination between cloudy and clear pixels.

However, this detection method has a cost, because it requires to process the data in chronological order and therefore prevents processing the image independently. It complicates the processing center and also affects the parallelization of processing. However, this method is implemented in MUSCATE center, to process SPOT4 (Take5), LANDSAT, Venμs and Sentinel-2 time series.

For more details on this method, used in MACCS Level 2A processor :

Hagolle, O., Huc, M., Villa Pascual D., & Dedieu, G. (2010). A multi-temporal method for cloud detection, applied to FORMOSAT-2, VENµS, LANDSAT and SENTINEL-2 images. Remote Sensing of Environment, 114(8), 1747-1755.
Detection of high clouds using an absorption band

Plane contrails will be much easier to detect with the new 1380nm band available on Landsat 8 and Sentinel-2.

On Landsat 8 and Sentinel-2,  a new spectral band is available, at 1380 nm. This spectral band corresponds to a strong water vapour absorption band. At this wavelength, the solar radiation is totally absorbed in his back and forth between the top of the atmosphere and the surface. In contrast, the radiation reflected by a cloud above 3000 meters is not totally absorbed as water vapor is mainly located in the lower layers of the atmosphere. Therefore, a simple threshold on the reflectance of this band enables to detect high clouds. Cirrus clouds are usually very difficult to detect, it will not be the case with this method which is also used within MUSCATE for LANDSAT-8 and Sentinel-2 satellites.

 

Thermal Infrared detection

High clouds are usually colder than the surface, the presence of a thermal band on Landsat satellites enables to use this property as a detection criterion. However, the thermal variations of the earth surface from a day to another are large, and prevent from detecting low clouds which have a temperature close to that of earth surface. We have not used this method as it applies only to LANDSAT.

 

3D detection

The Venµs satellite has two identical bands that observe scenes from two slightly different angles. This couple of bands makes it possible to see the terrain in 3D, with a moderate accuracy, but sufficient to tell the clouds from the surface. We use this method to detect clouds on Venμs data, in addition to the multi-temporal method. It should detect clouds  more than 500 meters high, and most importantly, knowing the cloud altitude will help detecting shadows.

 

Shadow detection

To be continued

First Level 2A time series of SPOT4 (Take5) images

(aerosol images have been added at the end of the post)
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The verification of the various steps of our SPOT4(take5) processing scheme is going on. On Thursday, we received our first time series, I orthorectified them on Friday, and we were then able to start testing our level 2A processor with the first time series. The one displayed below was obtained on the CESBIO site in Tensift valley : Marrakech is near the center of the image, while the Atlas mountains are in the South East part of the image.

The images on the left column are ortho-rectified, and expressed in Top of Atmosphere reflectance (Level 1C product), while the right column displays the same images after atmospheric correction and cloud detection (Level 2A products), produced by Mireille Huc (CESBIO).

We quickly figured out that the cloud detection would be easy on these very clear images, even if on the February 10th, several diffuse plane contrails can be hardly seen but are partially detected, and some of their shadows as well (clouds are circled by red lines, while shadows are circled by a black line). No false cloud detection is visible. Water bodies and snow are also correctly detected for this first try (circled in blue and purple respectively)

The atmospheric correction, based on a multi-temporal method that detects the aerosols, enabled to detect that the image of February the 5th was hazier than the images of January 31st and February 10th.The February 5th image (left column) has a subtle blueish haze compared to the other dates. On the right column, the tint is roughly constant from one image to the other, which means that the aerosol detection and the atmospheric correction are working well. The aerosol images provided below are also very consistent, with the Atlas mountains playing their role of physical barrier blocking the aerosols on either side of the images. There is an aerosol measurement station on this site but it broke down at the end of January, just for the start of the experiment : Murphy's law...

So, we have reviewed and tested all the steps of the processing, but we still have to check that our methods are sufficiently robust to handle correctly the very diverse situations offered by the 42 sites. How do you say, in English "ce n'est pas une mince affaire" ?

Level 1C products expressed in reflectance at the top of atmosphere.
(c) CNES, processing : CESBIO
Level 2A products expressed in surface reflectance after atmospheric correction
(c) CNES, processing : CESBIO

Aerosol optical thickness images are displayed below. One can note that the image of the February 5th is consitent with a lot of aerosols in the North of the Atlas, and nearly no aerosols in the South. The mountains often act as barriers for the aerosols witch usually stay at a low altitude. The orange dots correspond to the snow mask whereas the red ones correspond to the cloud mask. The brighter spots on the last image may be artifacts.

The orthorectification : how it works

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The "orthorectification" is a geometrical correction of images that aims at presenting them as if they had been captured from the vertical (in the remote sensing community, we say from "Nadir"), In practice, it transforms the satellite picture in an image that can be regiistered on a map.

 

To do that, the raw (L1A) product provides us with a lot of information

  • we know where the satelllte was when the picture was taken
  • we know how it the satellite is oriented
  • we know how the instrument is oriented in the satellite.

 

On recent satellites (Pleiades), the accuracy of this information allows positioning pixels to better than 10 meters. This is not the case for SPOT4, for which the standard deviation of the positioning accuracy is around 400 meters.

SPOT4 Level 1A image with a raw geometry (in Angola) SPOT4 Level 1C orthorectified image

 

In the case of SPOT4, we must "register" the images, using ground control points (GCP).  To take a GCP is to link a pixel of the image to a point on the map. You can create a GCP manually by identifying, for example, the same crossroads on the map and the image. Fortunately, you can also do this automatically using a technique called "automatic image matching", that I will not describe here.

 

For this, we use a reference image accurately located,  and a good digital terrain model (a relief map). The method we use is as follows:

  • From the reference image and the information provided by the satellite (the "ancillary data"), we simulate the image that should have been observed by SPOT4 if these ancillary data were accurate
  • We use automatic image matching to measure shifts between the simulated image and the actual image.
  • We deduce how the auxiliary data need to be corrected to remove these offsets
  • We are the able to find the location of all the points in the map within the L1A satellite image
  • Finally, the map is created by interpolation

 

All these operations are carried out using a software developed by CNES, called SIGMA. SIGMA is not distributed outside CNES, but many other frameworks exist among which the OTB, which is also a CNES tool.

 

For the SPOT4(Take5) sites located in France, we use a reference image made by the GEOSUD project  (a component of the French National Land Data Center), covering the whole of France and obtained from RapidEye satellite data. The orthorectification of RapidEye data was conducted by IGN, and its localization performance is very good.

 

Outside France, we do not have such a reference, and we decided to use data from LANDSAT satellites : the quality of positioning of LANDSAT data honorable, though at a lower level than GEOSUD (about 30 meters), but it has the main advantage of being available worldwide.

 

The orthorectification of a SPOT4(Take5) image takes 10 minutes on our computers (using only one core).

 

In more details :

  • Baillarin, S., P. Gigord, et O. Hagolle. 2008. « Automatic Registration of Optical Images, a Stake for Future Missions: Application to Ortho-Rectification, Time Series and Mosaic Products ». In Geoscience and Remote Sensing Symposium, 2008, 2:II‑1112‑II‑1115. doi:10.1109/IGARSS.2008.4779194.

Première mosaïque sur le site SudMiPy / 13 images mosaic on SudMipy site

Mosaique de 13 images ortho-rectifiées exprimées en réflectance au sommet de l'atmosphère. Il s'agit bien sûr d'une image sous échantillonnée, l'image entière fait 1.3 GO, et 14000*12000 pixels. Sur cette composition colorée (Rouge,PIR,MIR), la neige apparaît en bleu et se distingue bien des nuages


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Et voici la première ortho-image (N1C) fusionnant les 13 images prises par SPOT4 sur le site SudMiPy, les 16 et 17 février. La zone couvre 280*160 km². Les 13 images de Niveau 1A ont été livrées par SpotImage ce matin, et nous avons produit les ortho-images dans l'après midi, en utilisant le prototype du centre de production MUSCATE du Pôle Thématique Surfaces Continentales (seule la supervision des traitements se fait encore à la main, plus pour très longtemps)

bleu

Comme prévu, l'image est totalement claire, à part quelques brouillards dans la vallée de la Garonne et quelques cirrus sur l'ouest des Pyrénées (Au nord-est et au sud, il s'agit de neige).
Les observateurs attentifs auront remarqué la frontière entre la zone acquise le 16 et celle acquise le 17. Cette frontière est due en partie aux effets directionnels et en partie aux effets atmosphériques. Je vous en reparlerai une autre fois.


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Here is the first ortho-image (Level 1C) obtained from the 13 images taken by SPOT4 above the SudMiPy site in the South West of France, on the 16th and 17th of February 2013. The Level 1A images were delivered by SpotImage this morning, and we processed them this afternoon using the prototype of MUSCATE processing center. Only the scheduling of the processing was hand made, but we will soon have an automatic scheduler.

SPOT4 (Take5) / Progress report

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SPOT4(Take5) experiment started two weeks ago, here is a progress report :

  • Image acquisitions are progressing nominally, but the weather above France is very poor. Other sites are much better off.
  • Production of Level 1A images started at SpotImage. It is done once a week, on Thursdays. Accounting for the delay before image download, up to 2 weeks may happen between an image acquisition and level 1A product delivery.
  • First ortho-images have been generated, and the fusion of 4 SPOT4 images works fine and almost seamlessly.
  • As soon as we get our first time series above a given site, we will start testing and tuning the Level 2A methods (Cloud detection, atmospheric corrections)
  • The MUSCATE processing centre of the French Land Thematic Centre started its adaptation to SPOT4. Modifications will take a few weeks, and after that we will be able to start operational production.

First SPOT4(Take5) Level 1C (hand made), obtained in Provence (France), from a mosaic obtained from 4 SPOT4 images acquired simultaneously and ortho-rectified.

Lancement réussi pour Landsat 8 / Successful launch for Landsat 8

(English Version)

La NASA vient de réussir parfaitement le lancement de LANDSAT 8.  A la fin de sa période de vérification et étalonnage en orbite (au CNES, on dit "recette en vol"), dans environ 3 mois, les données de Landsat 8 seront distribuées gratuitement par l'USGS. L'objectif minimal de Landsat 8 est de fournir au moins une image claire par saison sur toutes les terres émergées.

Chaque point des USA sera observé tous les 16 jours, mais dans le reste du monde, les données seront un peu moins fréquentes, et les acquisitions seront tentées ou non en fonction des prévisions météorologiques et de la dernière observation claire disponible. L'immense intérêt de Landsat est la disponibilité de données depuis 40 ans.

Le Pôle Thématique Surface Continentales devrait mettre à disposition des utilisateurs des produits de Niveau 2A basés sur Landsat 8 avant la fin 2013.

Continue reading

As a clockwork

(version française)

So far, so good for SPOT4 (Take5) experiment ! First images were acquired yesterday (January the 31st), and will be downloaded to earth tomorrow (February the 2nd), but moreover, CNES programmed two acquisitions this morning followed by a download, so that we may check that everything goes well before the week-end. And, as a matter of fact...

...everything went as a clockwork : the download, inventory, upload to Astrium catalogue, and level 1A production. One of the pictures was taken above Ukraine, and the other one above Kuwait. One of them was cloudy, here is the other one.

SPOT4 (Take 5) first image over Kuwait (undersampled extraction)

 

 

SPOT4 a rejoint sa nouvelle orbite / SPOT4 is on its new orbit

C'est fait ! L'expérience SPOT4 (Take 5) a démarré hier soir ! Le changement d 'orbite a eu lieu en début de nuit, et les passages au dessus des stations de réception du réseau 2 Ghz du CNES ont confirmé que l'orbite visée a bien été atteinte. Un grand MERCI aux personnes du CNES (DCT/OP) et de CS qui y ont consacré une bonne partie de leur nuit. (L.Houpert, JP Chognard, M.Moulin, F.Rimbert, J.Sarda, S.Ramos, D. Delmas et G.Beaumet).

Done ! SPOT4 (Take5) started yesterday night. The orbit change occurred at the beginning of the night, and the overpasses above CNES 2Ghz station network confirmed that the expected orbit has been reached. Many thanks to all the people at CNES (DCT/OP) and CS who spent there a large part of their night. (L.Houpert, JP Chognard, M.Moulin, F.Rimbert, J.Sarda, S.Ramos, D. Delmas et G.Beaumet).

Oops !

Although we are Space Engineers that talk with satellites everyday, we still can forget that January has 31 days. I just updated my post "When will SPOT4 observe my site ?", because the day 1 of Take 5 cycle will not be February the 1st, but January  the 31st. If you had planned in-situ measurements simultaneously to the satellite overpass, you will need to reprogram them one day earlier. Our deepest apologies !

SPOT4 (Take5) : what's next ?

(Version Française)
Orbit Change

Tomorrow, January the 29th at night, the altitude of SPOT4 will be lowered by 2.5 km. This operation is not far from the regular manoeuvres of orbit control and should not be risky. During the night, the orbit parameters will be measured and checked by our colleagues of the Operations Sub Directorate at CNES (DCT/OP).

Programming first acquisitions

Image programming schedule will be uploaded on the satellite on the afternoon of January the 30th by our CNES DCT/OP colleagues. If everything works well, first images will be acquired on Wednesday, January 31st (Day 5 in the 5 days cycle). The images will be recorded on-board and downloaded on Toulouse receiving station on the2nd or 3rd of February, along with all the images collected in between.

Data Inventory

Astrium Geo (ex-Spot-Image) will upload the images in its internal catalogue (4th or 5th of February). We will be able to check them then.

Image production

First level 1A should be produced shortly afterwards by Astrium.  For the MUSCATE Production Center Teams at CNES and CESBIO, it will be the start of the final integration of level 1C and level 2A processors. As Take 5 experiment was only decided on the 11th of December,  the integration of the elementary processors (ortho-rectification, calibration, cloud detection, atmospheric correction), and their fine tuning will take a while.

Stay Tuned !