From GIS to Remote Sensing
This post is about a major update for the Semi-Automatic Classification Plugin for QGIS, version 4.8.0.
-added tab for searching and downloading Sentinel-2 images from https://scihub.esa.int/dhus/
Sentinel-2 is a new European satellite (read the handbook here), 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 8B -
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
|
These characteristics are comparable to Landsat images, and should allow for very accurate identification of land cover classes, especially vegetation.
A free registration is required in order to access to ESA data, see https://scihub.esa.int/userguide/1SelfRegistration .
In the SCP interface insert the user name and password and start searching and downloading the images. The search is performed using the Data Hub API.
It is possible to perform queries based on image acquisition date, geographical area, and image ID (name).
Then, it is possible to show an image preview directly in QGIS and download the selected images. Downloaded images (Level-1C) are already in Top-of-atmosphere reflectance values and converted to TIF format.
For the use of these images with SCP, it is recommended the creation of a virtual raster with the highest resolution (i.e. 10m), which can be used as input image in SCP. For general classifications, bands 1, 9, and 10 could be excluded from the band set.
Following a brief video that illustrates these functions.
So, welcome to Sentinel-2!
For any comment or question, join the Facebook group and a Google+ Community about the Semi-Automatic Classification Plugin.