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Found 3 results

  1. Dear all I'm new in remote sensing and I have problems when try to extract built-up area from an image or during image classification. I am using landsat 7 ETM+ and TM images, when I use supervised or un-supervised methods for image classification, urban area (built-up area) are not recognizable from bare-soil. I read several papers about built-up Indexes and tried some of them but there is no tangible improvement in results. Please guide me as step by step process. Regards
  2. 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
  3. Hi GIS Area, I just made this account wondering if is anybody here could help me making a simple classification on high resolution satelite imagery (GeoEye). The problem is that the parameters in the software are not so clear for me, both, unsupervised and supervised, and I haven't found any conclusive solution on the web. The methods I've tried are the K-mean, which gives me a highly fragmented image, and also ISOData, the parameters were all executed in the default, the only thing I did was to change classes from 5 to 3, or in the ISOData case, 3 or 4. The supervised class. asks
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