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The accuracy of supervised image classification is highly dependent upon several factors such as the design of training set (sample selection, composition, purity and size), resolution of input imager...
With a lot of successful applications of neural network-based classification, it has been recognized the classification can produce more accurate results than conventional approaches for remotely-sens...
This paper presents a study on automated habitat delineation and classification using very high spatial resolution (VHSR) optical remote sensing data in an alpine environment. Two overlapping study si...
We compared three multi-resolution merging techniques for classifying land cover and land condition in the central coast of California using Landsat7 imagery. We preferred the Principal Components t...

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