Road to the Semi-Automatic Classification Plugin v.8: Landsat and Sentinel-2 images download and preprocessing, classification

This is the second post describing the main new features of the new version 8 (codename "Infinity") of the Semi-Automatic Classification Plugin (SCP) for QGIS, which will be released in October 2023.
The new version is based on Remotior Sensusa new Python processing framework.

The tool "Download products" has been updated to download Landsat and Sentinel-2 images from different services. In particular, through the service NASA Earthdata (registration required at it will be possible to download the Harmonized Landsat and Sentinel-2 which are surface reflectance data product (generated with Landsat 8, Landsat 9, and Sentinel-2 data) with observations every two to three days at 30m spatial resolution (for more information read here). This is therefore a great source for frequent and homogeneous monitoring.
Moreover, Copernicus Sentinel-2 images will be searched through the Copernicus Data Space Ecosystem API, while the images are downloaded through the Google Cloud service that provides the free dataset as part of the Google Public Cloud Data program.
Other download services that were available in SCP 7 (e.g. Sentinel-1, ASTER images) will be available with future updates.

A new tool "Image conversion" provides a unified interface for preprocessing images to convert the digital values to surface reflectance. At the moment the preprocessing is available for Landsat and Sentinel-2 images, and other sensors will be included in the future.

The "Classification" tool has been updated with the algorithms provided by Remotior Sensus, in particular the addition of machine learning algorithms: Multi-Layer Perceptron, Support Vector Machine, and Random Forest that are available through scikit-learn and PyTorch.
This tool will allow for training the classifier, optionally saving the classifier for later use, and of course performing the classification.
Also, it will be possible to create classification previews on part of the image. 

Other posts about the new features will follow soon.

For any comment or question, join the Facebook group or GitHub discussions about the Semi-Automatic Classification Plugin.

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