Major Update: Semi-Automatic Classification Plugin v. 4.9.0 - Sentinel-2 Download and Conversion to Reflectance

This post is about a major update for the Semi-Automatic Classification Plugin for QGIS, version 4.9.0.


Following the changelog:
-updated the Sentinel-2 download for downloading single granules and selected bands
-updated the Sentinel-2 Pre processing tab for converting bands to TOA reflectance and surface reflectance (using DOS1)

This version allows for searching and downloading free Sentinel-2 images from the Copernicus website https://scihub.copernicus.eu/dhus . In particular, it is now possible to download single granules (or tiles) and choose which bands to download.


If the option "Pre process images" is checked, it is possible to download multiple granules and convert all the bands to reflectance.
In addition, it is possible to convert automatically the downloaded bands to TOA reflectance, or surface reflectance (using the DOS1 method). It requires the metadata file of the product (an xml file containing MTD_SAFL1C in the name thereof) to be included in the directory containing the Sentinel-2 bands.


Following, a brief video about this new tools.



Sentinel-2 is a new European satellite developed in the frame of Copernicus land monitoring services, which acquires 13 spectral bands with the spatial resolution of 10m, 20m and 60m depending on the band (see the following table).


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

The spatial and spectral characteristics of Sentinel-2 are designed for the discrimination of land cover materials, especially using supervised classifications. These numerous bands are very useful for land cover monitoring, allowing for the accurate calculation of spectral signatures (some examples in the following image).


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