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Unsupervised Classification Help


stephenhann

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I am using Erdas Imagine 2015 software to perform an unsupervised classification of a Landsat 8 img file. When using the Isodata method is there any parameters I can adapt such as standard deviation, convergence threshold etc that are a standard to produce the most accurate results for a land cover assessment rather than the default settings. As recoding and masking individual classes is a lengthy and complicated process.

Thanks

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