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Accuracy Assessment for Soft Classification Maps

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Gomez, Daniel and Biging, Greg and Montero, Javier (2013) Accuracy Assessment for Soft Classification Maps. In Remote Sensing of Natural Resources. Remote Sensing Applications Series (57). CRC Press, USA, pp. 57-66. ISBN 9781466556928

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Abstract

An important topic in using maps derived from a statistical classifier is the accuracy assessment of the classification. Analysts usually need to compare various techniques, algorithms, or different approaches. As pointed out by Stehman and Czaplewski (1998), the accuracy assessment of classification maps generally involves three different steps: the sampling design, the response or measurement design to obtain the true classes for each sampling (usually requiring an expert), and the analysis of the data obtained. In the ...


Item Type:Book Section
Subjects:Sciences > Mathematics > Mathematical statistics
ID Code:28566
Deposited On:20 Feb 2015 11:38
Last Modified:18 Apr 2016 16:58

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