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Let's narrow down the methods of classification to two major groups: object-oriented classification and pixel-based classification. The attached tables are from a publication titled Comparison of Pixel-Based and Object-Oriented Classification Approaches using Landsat-7 ETM sPECTRAL Bands. The highlighted row in Table 3 shows that object-oriented ...


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Keep in mind - no one procedure is necessarily going to provide the "best result." Image interpretation is critical, both before and after classification. You will likely find urban areas misclassified as something else and non-urban areas classified as being urban. You have two basic approaches: 1) Supervised classification: this involves selecting ...


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While ArcGIS can certainly perform the work you want, if you have access to other software, I would use those. I have not used GRASS before for image classification, but I know it is more than capable. From my knowledge, Ecognition is more for object based classification. I have used ENVI for image classification a few years ago and it does the job really ...


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If you use ArcGIS you'll want the spatial analyst extension. The tutorials for image classification are pretty easy to follow, and the actual process is pretty easily followed with real world data (Landsat). Another source that may save you tons of work is from USDA. Google USDA NASS. The National Agriculture Statistics Service has a downloadable raster ...


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http://opticks.org/ Might be another good option, looks quite functional.



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