Supervised Image Classification with QGIS

Learn remote sensing in QGIS with this supervised image classification tutorial. This tutorial teaches you how to perform supervised image classification on Landsat 9 data using the QGIS semi-automatic classification plugin to create labels (regions of interest) with which you can train several different classification algorithms.
Full QGIS Remote Sensing Course: geospatialschool.com/courses/...
Step-by-step instructions: opensourceoptions.com/blog/su...

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[@DanielHardwick-pe7ro]

Thank you, this was really useful. I find your teaching style really user friendly! I followed the tutorial as I don't have the required extensions in ArcGIS, so doing this in QGIS was great. Do you have any tips on converting the output to vector whilst maintaining the ID classifications? Rather than converting to vector each created polygon just having a random ID which you then have to classify? Also, and this might be an entirely different video, but do you have any info on machine learning? What I mean is this is great to classify pixels, but obviously a reservoir and a river might end up as the same output due to both being same pixel value/blue. But is there a way to teach it to say this is a reservoir, based on pixel values and the shape, as opposed to this being a river, which has same or similar pixel value, but different shape? I haven't used QGIS in a while, so dusting off the cobwebs!

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