Cloud masking

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(Inspect a Sentinel-2 Level-2A Quality index data)
(Refining cloud mask)
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[[File:Qgis_cloud_qi_pseudo.png|400px]] [[File:Qgis_cloud_qi_opacity.png|300px]]
 
[[File:Qgis_cloud_qi_pseudo.png|400px]] [[File:Qgis_cloud_qi_opacity.png|300px]]
  
= Refining cloud mask =
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= Convert quality indicator band to a binary cloud mask =
 
* Create a binary cloud mask (bitmask) where clouds = 1 and non-clouds = 0. Use the Processing tool {{mitem|text= OTB --> Miscellaneous --> Band Math}}. Tick the single band QI layer in the '''Input Image list''' list. You may write a conditional ''ifelse expression'' using lazy operators. Type into the '''Expression''' field: {{typed|text=(im1b1>30)?1:0}}  If pixel values of band 1 of multiband image 1 are larger than 30 then replace with 1 otherwise replace with 0. The output pixel type is '''uint16'''.
 
* Create a binary cloud mask (bitmask) where clouds = 1 and non-clouds = 0. Use the Processing tool {{mitem|text= OTB --> Miscellaneous --> Band Math}}. Tick the single band QI layer in the '''Input Image list''' list. You may write a conditional ''ifelse expression'' using lazy operators. Type into the '''Expression''' field: {{typed|text=(im1b1>30)?1:0}}  If pixel values of band 1 of multiband image 1 are larger than 30 then replace with 1 otherwise replace with 0. The output pixel type is '''uint16'''.
 
[[File:Qgis_cloud_bandmath.png|500px]]]
 
[[File:Qgis_cloud_bandmath.png|500px]]]

Revision as of 15:03, 10 November 2020

Contents

Inspect Sentinel-2 quality index data

The exclusion of clouds and cloud shadow is an important processing step which is usually done in an early pre-processing stage. The Sentinel-2 products are annotated with Quality Indicators (QI_DATA).

If you use a Sentinel-2 Level 1C product, you'll find a rough dense cloud and cirrus mask (GML vector format) in the folder QI_DATA with the file name MSK_CLOUDS_B00.gml. The vector attribute column masktype distinguishes two classes: OPAQUE (dense clouds) and CIRRUS.

In case of a Sentinel-2 Level 2A product you may find a file in the folder QI_DATA with the extension _CLD_20m.jp2 (data type: 8bit unsigned integer, spatial resolution 20m) which might be used for masking clouds. Data range is from 0 for high confidence clear sky to 100 for high confidence cloudy (for more details see L2A Product Definition Document).

  • Load a multiband Sentinel-2 satellite image (Level 2-A product) Changing Raster Layer Style to display a true color (RGB = B4,B3,B2) and a standard false color composite (RGB = B8,B4,B3)
  • Zoom in to a cloudy part of the image and compare the extent of cloud and cloud shadow in both composites. Which composite is better for displaying clouds?

Qgis cloud tcc.png Qgis cloud fcc.png

  • Overlay the QI Cloud band on top of the color composites. Use the Identify Feature Tool for requesting pixel values of the QI band file inside a cloud. Which values represent clouds?
  • Change Render type Singelband pseudocolor
  • Interpolation is discrete.
  • Choose Color ramp spectral
  • Mode is equal with
  • Interval Classes is 10 as shown in the screenshot.
  • Double click on a color field of some classes {{mitem|text=Layer --> Properties --> Style) to open the change color window. Change the opacity from 100% to 0%. Find the threshold for clouds.

Qgis cloud qi pseudo.png Qgis cloud qi opacity.png

Convert quality indicator band to a binary cloud mask

  • Create a binary cloud mask (bitmask) where clouds = 1 and non-clouds = 0. Use the Processing tool OTB --> Miscellaneous --> Band Math. Tick the single band QI layer in the Input Image list list. You may write a conditional ifelse expression using lazy operators. Type into the Expression field: (im1b1>30)?1:0 If pixel values of band 1 of multiband image 1 are larger than 30 then replace with 1 otherwise replace with 0. The output pixel type is uint16.

Qgis cloud bandmath.png]

  • Apply a circular majority filter with a radius of 16 pixels. Open the Processing tool OTB --> Learning --> ClassificationMapRegularization. The input classifcation image is the Output Image of the band math operation step. Structering element radius is 16 pixels. Adjust Label for NoDat and undecided class. Specify a file name for the Output regularized image. Output pixel type is uint16.

Qgis cloud majority.png

  • Open the Processing tool OTB --> Feature Extraction --> BinaryMorphologicalOperation (dilate). Choose the Regularized image as input image. The structuring element type is ball with a radius of 21 pixelsOoutput pixel type is uint16

Qgis cloud dilate.png

  • Convert the Feature Output Imge from raster to vector format. Raster --> Conversion --> Polygonize. Select an output file name for vector polygons.

Qgis cloud polygonize.png

  • Change the display of the output vector polygon layer Layer properties --> Style --> Single Symbol --> Simple Fill --> Fill Style from Solid to No Brush. Change the Outline color to bright green and increase the Outline width. As background layer use a False Color Composite of the Sentinel-2 image.
  • Toggle editing Qgis vector edit.png of the resulting vector polygon layer. Activate Select polygons by dragging a box or by single click Qgis vector select.png, select all polygons with attribute DN = 0 or which are misclassified as clouds and delete them by pressing Del on your keyboard. Save your edits Qgis vector save.png.

Creating cloud shadow mask

  • Prepare a False color composite of the Sentinel-2 image as background layer in the canvas.
  • Right click on the edited polygon layer in the TOC. Choose Export --> Save features as.... Fill the form as shown below.

Qgis vector saveas.png

  • Mark the new created polygon layer in the TOC and toggle editing Qgis vector edit.png of the vector file. Select all polygons using Qgis vector select all.png or press Ctrl + A. Activate Edit --> Move feature(s) Qgis vector move.png. Left click on the canvas and move the cloud polygons that shadows on the background false color composite are completely covered. Save your edits Qgis vector save.pngand stop editing Qgis vector edit.png.
  • Select polygons Qgis vector select.png outside the image extent of the false color composite and delete them by pressing Del on your keyboard. Save your edits and stop editing Qgis vector edit.png.

Applying cloud and cloud shadow mask

  • Vector --> Data management tools --> Merge vector layers. as Layer to merge select the cloud and cloud_shadow polygon layers. Run.

Qgis vector merge.png

  • Create a polygon with the extent of the Sentinel-2 image: Create image extent polygon.
  • Vector --> Geoprocessing Tools --> Symmetrical difference. Input layers are the image extent and the merged cloud and cloud_shadow polygons.

Qgis vector symdiff.png

  • Apply the output vector layer Cleaned as mask to the multiband Sentinel-2 image file. Raster --> Extraction --> Clip Raster by Mask Layer.

Graphical Processing Tool Model

You can use a prepared graphical processing toolbox model. Download the file from Stud.IP:S2cloudDetection.model3.

  1. Open QGIS and go to the Processing Toolbox; if the Toolbox is not opened click Processing --> Toolbox to activate it. Once the Toolbox is opened go to Qgis-processing model iconExample.png Models --> Open existing models and load the previously downloaded model.
  2. The model should appear in the Models tab. Double click on it to execute.
  3. A window showing the different input and outputs should appear, just as if you were using any other geo-algorithm of the Processing Toolbox.
  4. You will just need to provide a multispectral Sentinel-2 image file with 10 ordered bands (B2, B3, B4, B5, B6, B7, B8, B8A, B11, B12).

Qgis s2 cloud detection model.png


Figure A: False color composite RGB=8,4,3
Figure B: False color composite RGB=8,4,3 masked with cloud and cloud shadow
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