Image Segmentation. A Completed Workflow From Training Samples Generation to Accuracy Assessment

Image classification for landcover mapping has so many types of algorithms or methods. One of them is Image Segmentation and Classification. The process can be described as imagery is segmented into many segments, and from there we classify them according to the specified classification schema. 

This video tutorial below is about how to perform object-based image segmentation and classification using Satellite Imagery data. Not only the segmentation, but I also made this video as a workflow, which means I demonstrate from the training samples generation (for supervised classification), ground truth creation data to support accuracy assessment, the image segmentation process, and closing with the accuracy assessment to inspect the accuracy of the final classified raster. Almost every step is automatic so it will save a ton of time and effort. 

So if you are curious, check this below

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