Interpretation of Remote Sensing Images


A supervised classification of remote sensing images is a processing technique that allows for the identification of materials in the image, according to their spectral signatures (see here for further definitions about remote sensing).
The main advantage of this approach is that an entire image can be processed rapidly, producing the land cover classification thereof.
This post is about the interpretation of remote sensing images that is a fundamental phase of the ROI creation, which is a required step for the semi-automatic classification.

Minor Update: Semi-Automatic Classification Plugin v. 2.2.2


New update of the Semi-Automatic Classification Plugin for QGIS 2 to version 2.2.2.

The changelog:

-compatibility with QGIS dev and Processing 2.0-20131029
-bugfix and code improvements

This is a minor update, which allows for the use of the Semi-Automatic Classification Plugin in QGIS dev and the experimental Processing 2.0-20131029.
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