Difference between revisions of "Clip Sentinel-2 images"

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[[File:Captura de ecrã de 2018-06-07 11-36-48.png]]
 
[[File:Captura de ecrã de 2018-06-07 11-36-48.png]]
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{|
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| Landsat 8 Bands || Wavelength [micrometers] || Resolution [meters]
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|-
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| Band 1 - Coastal aerosol || 0.43 - 0.45 || 30
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|-
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| Band 2 - Blue || 0.45 - 0.51 || 30
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|-
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| Band 3 - Green || 0.53 - 0.59 || 30
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|-
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| Band 4 - Red || 0.64 - 0.67 || 30
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|-
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| Band 5 - Near Infrared (NIR) || 0.85 - 0.88 || 30
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|-
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| Band 6 - SWIR 1 || 1.57 - 1.65 || 30
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|-
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| Band 7 - SWIR 2 || 2.11 - 2.29 || 30
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|-
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| Band 8 - Panchromatic || 0.50 - 0.68 || 15
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|-
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| Band 9 - Cirrus || 1.36 - 1.38 || 30
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|-
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| Band 10 - Thermal Infrared (TIRS) 1 || 10.60 - 11.19 || 100 (resampled to 30)
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|-
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| Band 11 - Thermal Infrared (TIRS) 2 || 11.50 - 12.51 || 100 (resampled to 30)
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|}
  
 
== Clip Band sets ==
 
== Clip Band sets ==

Revision as of 09:49, 7 June 2018

Sentinel-2 images are large and have many bands. We can minimize the processing time by restricting the images to the area we want to work on.

For this exercise, we can use the GADM data. Download Denmark's data from https://gadm.org/download_country_v3.html Or use this direct link: [1]

Create the polygon

From gadm36_DNK_2, create a unique polygon containing the 4 municipalities (kommuner):

  • Hillerød,
  • Helsingør,
  • Gribskov,
  • Fredensborg

Save the layer (using shapefile format) using EPSG:32633 as the CRS, to match the same CRS as the Sentinel-2 images we have.

Clipping polygon

The resulting layer "studyarea" should look like:

Captura de ecrã de 2018-06-06 15-32-20.png

Create a Band set (virtual raster) with Sentinel images

Now that we have both the study area polygon and the Sentinel-2 images stored on a folder, we clip all the images to make its processing faster.

To clip all the images, we use the SCP plugin → Preprocessing → Clip multiple rasters.

https://media.readthedocs.org/pdf/semiautomaticclassificationmanual/latest/semiautomaticclassificationmanual.pdf#subsubsection*.284

The clip tools needs a Band set to operate on. Since we will not use some bands (1, 9 and 10), we can create a band set without them.

Captura de ecrã de 2018-06-07 10-34-06.png

The new Band set is added to QGIS layers.

It is added with a default style. The default style uses the first 3 bands as the RGB bands. So, band 1 is used as Red, 2 as Green and 3 as Blue.

Change the style definition, to show the first 3 bands, but by a different order.

Remember that we are not using band 1, so our band 1 is in fact Sentinel band 2.

Sentinel-2 Bands Central Wavelength [micrometers] Resolution [meters]
Band 1 - Coastal aerosol 0.443 60
Band 2 - Blue 0.490 10
Band 3 - Green 0.560 10
Band 4 - Red 0.665 10
Band 5 - Vegetation Red Edge 0.705 20
Band 6 - Vegetation Red Edge 0.740 20
Band 7 - Vegetation Red Edge 0.783 20
Band 8 - NIR 0.842 10
Band 8A - Vegetation Red Edge 0.865 20
Band 9 - Water vapour 0.945 60
Band 10 - SWIR - Cirrus 1.375 60
Band 11 - SWIR 1.610 20
Band 12 - SWIR 2.190 20

Captura de ecrã de 2018-06-07 10-41-56.png

Create a second Band set (virtual raster) with Landsat 8 images

Captura de ecrã de 2018-06-07 11-36-48.png

Landsat 8 Bands Wavelength [micrometers] Resolution [meters]
Band 1 - Coastal aerosol 0.43 - 0.45 30
Band 2 - Blue 0.45 - 0.51 30
Band 3 - Green 0.53 - 0.59 30
Band 4 - Red 0.64 - 0.67 30
Band 5 - Near Infrared (NIR) 0.85 - 0.88 30
Band 6 - SWIR 1 1.57 - 1.65 30
Band 7 - SWIR 2 2.11 - 2.29 30
Band 8 - Panchromatic 0.50 - 0.68 15
Band 9 - Cirrus 1.36 - 1.38 30
Band 10 - Thermal Infrared (TIRS) 1 10.60 - 11.19 100 (resampled to 30)
Band 11 - Thermal Infrared (TIRS) 2 11.50 - 12.51 100 (resampled to 30)

Clip Band sets