Use of a dark object concept and support vector machines to automate forest cover change analysis

@inproceedings{Huang2008UseOA,
  title={Use of a dark object concept and support vector machines to automate forest cover change analysis},
  author={Chengquan Huang and Kuan Song and Sunghee Kim and John R. Townshend and Paul Davis and Jeffrey G. Masek and Samuel N. Goward},
  year={2008}
}
An automated method was developed for mapping forest cover change using satellite remote sensing data sets. This multi-temporal classification method consists of a training data automation (TDA) procedure and uses the advanced support vector machines (SVM) algorithm. The TDA procedure automatically generates training data using input satellite images and existing land cover products. The derived high quality training data allow the SVM to produce reliable forest cover change products. This… CONTINUE READING
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