Is there a preferred classifier for operational thematic mapping?
The importance of properly exploiting a classifier's inherent geometric characteristics when developing a classification methodology is emphasized as a prerequisite to achieving near optimal performance when carrying out thematic mapping. When used properly, it is argued that the long-standing maximum likelihood approach and the more recent support vector machine can perform comparably. Both contain the flexibility to segment the spectral domain in such a manner as to match inherent class...[Show more]
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|Source:||IEEE Transactions on Geoscience and Remote Sensing|
|01_Richards_Is_there_a_preferred_2014.pdf||500.62 kB||Adobe PDF||Request a copy|
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