Mosaïques optiques#

Combine images to create single raster datasets with optical mosaics

Aperçu#

A mosaic is a combination or fusion of two or more images. In SEPAL, you can create a single raster dataset from several raster datasets by mosaicing them together. This can be achieved on both contiguous rasters (see first image below) and overlapping images (see second image below).

Ces zones de superposition peuvent être gérées de différentes manières. Par exemple, vous pouvez choisir de:

  • ne conserve que les données matricielles du premier ou dernier jeu de données ;

  • combiner les valeurs des cellules de superposition à l’aide d’un algorithme de pondération ;

  • moyenner les valeurs des cellules de superposition ; ou

  • prend la valeur maximale ou minimale.

En outre, certaines corrections peuvent être apportées à l’image pour tenir compte des nuages, de la neige et d’autres facteurs; ces opérations sont complexes et répétitives.

SEPAL vous offre un moyen interactif et intuitif de créer des mosaïques dans n’importe quel zone d’intérêt (AOI).

Note

Vous ne pourrez pas récupérer les images si vos comptes SEPAL et Google Earth Engine (GEE) ne sont pas connectés. Pour plus d’informations, allez dans Use GEE with SEPAL.

Début#

Once the mosaic recipe is selected, SEPAL will display the recipe process in a new tab (see 1 in the image below) and the AOI selection window will appear in the lower right (2).

La première étape est de changer le nom de la recette. Ce nom sera utilisé pour identifier vos fichiers et recettes dans les dossiers SEPAL. Utilisez la convention la mieux adaptée à vos besoins. Double-cliquez simplement sur l’onglet et écrivez un nouveau nom. Il sera par défaut à Optical_mosaic_<start_date>_<end_date>_<band name>.

Note

L’équipe SEPAL recommande d’utiliser la convention suivante : <aoi name>_<dates>_<measure>.

Paramètres#

In the lower-right corner, five tabs are available, which allow you to customize the mosaic creation to your needs:

  • AOI: zone d’intérêt

  • DAT: date cible d’intérêt pour la mosaïque/composite

  • SRC: jeu de données source de la mosaïque/composite

  • SCN: paramètres de sélection de scène

  • CMP: paramètres de composition

Sélection de l’AOI#

Les données exportées par la recette seront générées à partir des limites de l’AOI. Il y a plusieurs façons de sélectionner l’AOI dans SEPAL:

  • Limites administratives

  • Tables EE

  • Polygones personnalisés

Ils sont décrits dans notre documentation. Pour plus d’informations, lisez Sélection de l’AOI.

Date#

Mosaïque annuelle#

In the DAT tab, select a year which pixels in the mosaic should come from. Then select the Apply button.

Mosaïque saisonnière#

Sélectionnez Plus dans le panneau DAT pour étendre l’outil de sélection de date. Plutôt que de choisir une année, vous pouvez choisir une saison d’intérêt.

Select the (1) to open the Date selection pop-up window. The selected date will be the target of the mosaic (i.e. the date from which pixels in the mosaic should ideally come from).

Using the main slider (2), define a season around the target date by identifying a start date and end date. SEPAL will then retrieve the mosaic images between those dates.

The number of images in a single season of one year may not be enough to produce a correct mosaic. SEPAL provides two secondary sliders to increase the pool of images to create the mosaic. Both count the number of seasons SEPAL can retrieve in the past (Past season - [3]) and in the future (Future season - [4]).

When the selection is done, select the Apply button.

Sources#

Comme mentionné dans l’introduction, une mosaïque utilise différents ensembles de données matriciels qui peuvent être obtenus à partir de sources multiples. SEPAL vous permet de sélectionner des données à partir de plusieurs points d’entrée. Ci-dessous, vous pouvez trouver une description de ces sources (sélectionnez un lien pour voir les informations du jeu de données correspondant):

  • L8: Landsat 8 Tier 1. Landsat scenes with the highest available data quality are placed into Tier 1 and considered suitable for time-series processing analysis. Tier 1 includes Level-1 Precision Terrain (L1TP) processed data that have well-characterized radiometry and are intercalibrated across different Landsat sensors. The geo-registration of Tier 1 scenes will be consistent and within prescribed tolerances (< = 12 m root mean square error [RMSE]). All Tier 1 Landsat data can be considered consistent and intercalibrated (regardless of the sensor used) across the full collection.


  • L8 T2: Landsat 8 Tier 2. Scenes not meeting Tier 1 criteria during processing are assigned to Tier 2. This includes Systematic terrain (L1GT) and Systematic (L1GS) processed scenes, as well as any L1TP scenes that do not meet the Tier 1 specifications due to significant cloud cover, insufficient ground control and other factors. Users interested in Tier 2 scenes can analyze the RMSE and other properties to determine the suitability for use in individual applications and studies.


  • L7: Landsat 7 Tier 1. Landsat scenes with the highest available data quality are placed into Tier 1 and are considered suitable for time-series processing analysis. Tier 1 includes Level-1 Precision Terrain (L1TP) processed data that have well-characterized radiometry and are intercalibrated across different Landsat sensors. The geo-registration of Tier 1 scenes will be consistent and within prescribed tolerances (< = 12 m RMSE). All Tier 1 Landsat data can be considered consistent and intercalibrated across the full collection (regardless of the sensor used).


  • L7 T2: Landsat 7 Tier 2. Scenes not meeting Tier 1 criteria during processing are assigned to Tier 2. This includes Systematic terrain (L1GT) and Systematic (L1GS) processed scenes, as well as any L1TP scenes that do not meet the Tier 1 specifications due to significant cloud cover, insufficient ground control and other factors. Users interested in Tier 2 scenes can analyze the RMSE and other properties to determine the suitability for use in individual applications and studies.


  • L4-5: Landsat 4 Tier 1 combined with Landsat 5 Tier 1. Landsat scenes with the highest available data quality are placed into Tier 1 and are considered suitable for time-series processing analysis. Tier 1 includes Level-1 Precision Terrain (L1TP) processed data that have well-characterized radiometry and are intercalibrated across different Landsat sensors. The geo-registration of Tier 1 scenes will be consistent and within prescribed tolerances (< = 12 m RMSE). All Tier 1 Landsat data can be considered consistent and intercalibrated across the full collection (regardless of the sensor used).


  • L4-5 T2: Landsat 4 TM Tier 2 combined with Landsat 5 TM Tier 2. Scenes not meeting Tier 1 criteria during processing are assigned to Tier 2. This includes Systematic terrain (L1GT) and Systematic (L1GS) processed scenes, as well as any L1TP scenes that do not meet the Tier 1 specifications due to significant cloud cover, insufficient ground control and other factors. Users interested in Tier 2 scenes can analyze the RMSE and other properties to determine the suitability for use in individual applications and studies.


  • A+B: Sentinel-2 Multispectral instrument is a wide-swath, high-resolution, multispectral imaging mission supporting Copernicus Land Monitoring studies, including the monitoring of vegetation, soil and water cover, as well as the observation of inland waterways and coastal areas.

To validate your selection, select the Apply button.

Scènes#

Note

Si les données Sentinel et Landsat ont été sélectionnées, vous serez forcé d’utiliser toutes les scènes. Comme le système de tuilage de Sentinel et Landsat est différent, il est impossible de sélectionner des scènes à l’aide de l’outil présenté dans les sections suivantes.

Vous pouvez utiliser plusieurs options pour sélectionner les meilleures scènes de votre mosaïque. Le plus simple est d’utiliser toutes les images disponibles en fonction des paramètres de date. Sélectionnez Utilisez toutes les scènes et toutes les images seront intégrées dans la mosaïque.

Choisissez Selectionner les scènes et choisissez l’une des trois options Priorité disponibles en fonction des besoins de votre analyse (SEPAL trie les images disponibles pour chaque tuile) :

  • Cloud free: Priorise les images avec zéro ou peu de nuages.

  • Target date: Prioritizes images that match the target date.

  • Equilibré: Priorise les images qui maximisent à la fois l’absence de nuage et la date de cible.

To validate your selection, select the Apply button.

Composite#

Note

This step is optional. SEPAL provides the following options by default:

  • Correction : SR, BRDF

  • Filtres Pixels : Pas de filtres

  • Détection de nuage: Bandes QA, Score Cloud

  • Masquage des nuages: Modéré

  • buffer de nuage: Aucun

  • Masquage des neiges : Activé

  • Composition de la méthode: Medoid

To create a mosaic, provide SEPAL with the compositing method to create the final image. See the following image for all possible compositing options available.

Corrections#

Cela appliquera des corrections sur les pixels empilés pour améliorer la qualité de la mosaïque.

  • SR: Surface reflectance improves comparison between multiple images over the same region by accounting for atmospheric effects such as aerosol scattering and thin clouds, which can help in the detection and characterization of Earth surface change. Top-of-atmosphere images are used if not selected.

  • BRDF: Uses a bidirectional reflectance distribution function (BRDF) model to characterize surface reflectance anisotropy. For a given land area, the BRDF is established based on selected multi-angular observations of surface reflectance.

  • Calibrate: Calibre les données de Sentinelle et de Landsat pour les rendre compatibles.

    Note

    Cette option n’est disponible que si :

    • Les données de Landsat et de Sentinelle sont mélangées ; et

    • BRDF and surface reflectance (SR) corrections are disabled.

Filtres des pixels#

Activating any of the filters will remove some pixels from the stack. Removing pixels improves the quality of the mosaic, as they are not taken into account in the median value computation.

Note

Each filter is applied iteratively (e.g. if the normalized difference vegetation index [NDVI] is already filtering all pixels but one, there will be nothing left in the stack to be filtered by day of year).

Note as well that adding filters significantly increases the creation time of the mosaic.

  • Shadow: Filters the XX percent darkest pixels of the stack.

  • Haze: Computes a haze index and filters the XX percent highest values.

  • NDVI: Computes the NDVI and only keeps the XX percent highest values.

  • Day of the year: Computes the distance from target day in days and filters out the XX percent farthest.

Détection des nuages#

Refers to the algorithm used to detect clouds.

  • QA bands: Uses quality assessment (QA) bands to identify clouds in Sentinel data.

  • Cloud score: Uses the computed cloud score to identify clouds in Landsat data.

  • Pino 26: Uses the Pino_26 algorithm to identify clouds (for more information, see D. Simonetti [2021]).

    Note

    This filter is only available for Sentinel exclusive source when both BRDF and SR correction are disabled.

Masquage des nuages#

Contrôle comment les nuages seront masqués en fonction de l’algorithme de détection du nuage sélectionné.

  • off: Uses cloud-free pixels if possible, but doesn’t mask areas without cloud-free pixels.

  • moderate: Relies only on image source QA bands for cloud masking (a moderate threshold is used).

  • aggressive: Relies on image source QA bands and a cloud scoring algorithm for cloud masking with an aggressive threshold (this will probably mask out some built-up areas and other bright features).

Cloud buffering#

When pixels are identified as clouds, SEPAL can remove pixels in a small buffer around it to prevent hazy pixels at the borders of clouds to be included in the mosaic.

Note

Buffering is done on the pixel level, so using this option will significantly increase the creation time of the mosaic.

  • none: Doesn’t use cloud buffering.

  • moderate: Masks an additional 120 m around each larger cloud.

  • aggressive: Masks an additional 600 m around each larger cloud.

Masquage de la neige#

Définit comment les pixels enneigés seront masqués.

  • on: Masks snow. This tends to leave some pixels with shadowy snow.

  • off: Doesn’t mask snow. Note that some clouds might get misclassified as snow; therefore, disabling snow masking might lead to cloud artifacts.

Méthode de composition#

After filtering the stack of pixels, SEPAL will compute the median value on the different bands of the image. The composing method will define how the final pixel value is extracted.

  • Medoid: Uses the closest pixel from the median value. As a real pixel from the stack, the final value will embed metadata (e.g. the date of observation).

  • Median: Uses the computed value of the median. If no pixel is matching this value, the pixel will not embed any metadata. It tends to produce smoother mosaics.

Analyse#

After selecting the parameters, you can start interacting with the scenes and begin the analysis.

In the upper-right corner, three tabs are available, which allow you to customize the mosaic scene selection and export the final result:

  • : auto-select scenes

  • : clear selected scenes

  • : retrieve mosaic

Note

If you have not selected the option Select scenes in the SCN tab, the button will be disabled and the scene areas will be hidden as no scene selection needs to be performed (see those with a number in a circle on the previous screenshot).

If you can’t see the image scene area, you probably have selected a small AOI. Zoom out on the map and you will see the number of available images in the circles.

Sélectionner les scènes#

To create a mosaic, select the scenes that will be used to compute each pixel value of the mosaic. SEPAL provides a user-friendly interface that will guide you through the selection process. You don’t have to select the stack for every pixel; instead, SEPAL will clip the AOI in smaller pieces called Tiles. These tiles correspond to the native tiling system of your dataset and are displayed on the map with circled numbers in their centroid. Each number corresponds to the number of scenes available to build the mosaic tile. Hover over these circles to see the tile boundaries appear.

Note

Landsat and Sentinel datasets have a different grid system, which is why the selection process cannot be used if you have selected both of these datasets. If you have an idea related to the user interface (UI) that could make them work together, let us know in our issue tracker.

Auto-select scene#

Selecting the tab will open the Auto-selection pane.

Move the sliders to select the minimum and the maximum number of scenes SEPAL should select in a tile. Then, select the Validate button to apply the auto-select method.

SEPAL will use the priority defined in the SCN tab to order the scene and collect the optimal number for your request.

Note

The result is never perfect but can be used as a starting point for the manual selection of scenes.

Clear all scenes#

If at least one scene is selected, the tab will be available. Select it to open the Clear pane.

Select Clear scenes to remove all manually and automatically selected scenes.

Manual selection#

To open the Scene selection menu, hover over a tile circled-number and select it (1). The window will be divided into two sections:

  • Available scene (2): All the available scenes according to the parameters you selected. These scenes are ordered using the priority parameter you set in the SCN tab.

  • Selected scenes (3): The scenes that are currently selected.

Each thumbnail represents a scene of the tile stack. You have the option to include them in the mosaic. The scenes located on the left side are the Available scenes; the Selected scenes are on the right side. In both cases, the following information can be found on the thumbnail:

  • A small preview of the scene in the red, blue, green band combination.

  • The exact date in YYYY-MM-DD of the scene.

  • The satellite name .

  • The cloud coverage of the scene in percent and its position in the stack values .

  • The distance from target day in days within the season and its position in the stack values .

You can decide to move the scene to the Selected scene area by selecting Add or moving it back to Available scene pane by selecting Remove.

Astuce

Scenes are moved from one side to the other so they are not duplicated and cannot be selected twice. Be careful if your connection is slow; wait for the thumbnail to move before clicking again (if you click too fast, you could select two different images instead of one).

Once you are happy with your selection, select the Apply button to close the window and use the selected scenes to compute the mosaic on this tile. When the window is closed, SEPAL resets the rendering of all tiles.

Retrieve#

Important

You cannot export a recipe as an asset or a .tiff file without a small computation quota. If you are a new user, see Gérer vos ressources.

Selecting the tab will open the Retrieve pane where you can select the exportation parameters.

Bands#

You need to select the band(s) to export with the mosaic. There is no maximum number of bands, but exporting useless bands will only increase the size and time of the output. To discover the full list of available bands with SEPAL, see Optical Satellite bands, transformations, and indices.

Astuce

There is no fixed rule to the band selection. Each index is more adapted to a set of analyses in a defined biome. The knowledge of the study area, the evolution expected and the careful selection of an adapted band combination will improve the quality of downstream analysis.

Dates#

  • dayofyear: the Julian calendar date (day of the year)

  • dayfromtarget: the distance to the target date within the season in days

Échelle#

You can set a custom scale for exportation by changing the value of the slider in metres (m) (note that requesting a smaller resolution than images” native resolution will not improve the quality of the output – just its size – keep in mind that the native resolution of Sentinel data is 10 m, while Landsat is 30 m.)

Récupérer vers#

You can export the image to the SEPAL workspace or to the ;guilabel:Google Earth Engine Asset folder. The same image will be exported to both; however, for the former, you will find it in .tif format in the Downloads folder; for the latter, the image will be exported to your GEE account asset list.

Note

If Google Earth Engine Asset is not displayed, it means that your GEE account is not connected to SEPAL. Please refer to Connect SEPAL to GEE.

Select Apply to start the download process.

Statut d’exportation#

In the Tasks tab (lower-left corner using the or buttons, depending on the loading status), you will see the list of the different loading tasks. The interface will provide you with information about task progress and display an error if the exportation has failed.

Si vous n’êtes pas satisfait de la façon dont nous présentons les informations, la tâche peut également être surveillée en utilisant le Gestionnaire de tâches GEE.

Astuce

Cette opération fonctionne entre les serveurs GEE et SEPAL en arrière-plan. Vous pouvez fermer la page SEPAL sans arrêter le processus.

Lorsque la tâche est terminée, le cadre sera affiché en vert, comme indiqué sur la deuxième image ci-dessous.

Accès#

Une fois le processus de téléchargement terminé, vous pouvez accéder aux données dans vos dossiers SEPAL. Les données seront stockées dans le dossier Downloads en utilisant le format suivant :

.
└── downloads/
    └── <MO name>/
        ├── <MO name>_<gee tile id>.tif
        ├── <MO name>_<gee tile id>.tif
        ├── ...
        ├── <MO name>_<gee tile id>.tif
        └── <MO name>_<gee tile id>.vrt

Note

Understanding how images are stored in an optical mosaic is only required if you want to manually use them. The SEPAL applications are bound to this tiling system and can digest the information for you.

Les données sont stockées dans un dossier en utilisant le nom de la mosaïque optique telle qu’elle a été créée dans la première section de cet article. Comme le nombre de données est spatialement trop grand pour être exporté en même temps, les données sont divisées en morceaux plus petits et réunies dans un fichier <MO name>_<gee tile id>.vrt.

Astuce

The full folder with a consistent tree folder is required to read the .vrt

Important

Now that you have downloaded the optical mosaic to your SEPAL and/or GEE account, it can be downloaded to your computer using FileZilla or used in other SEPAL workflows.

Mis à jour le août 26, 2024.