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A study for Improvement the Accuracy of Tree Species Classification within Various Sizes of Training Sample Areas by Using the High-resolution Images
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  • Journal title : Journal of Wetlands Research
  • Volume 16, Issue 3,  2014, pp.393-401
  • Publisher : Korean Wetlands Society
  • DOI : 10.17663/JWR.2014.16.3.393
 Title & Authors
A study for Improvement the Accuracy of Tree Species Classification within Various Sizes of Training Sample Areas by Using the High-resolution Images
Hou, Jin Sung; Yang, Keum Chul;
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 Abstract
The purpose of this study was to investigate the objective impact in accuracy and reliability with tendency depend on training samples by using the high-resolution images. Supervised classification was performed based on multi-spectral images which made by each satellite and aerial images for considering all of bands' characteristics. The highest accuracy was 84.7% with satellite image(3*3) and 83% with aerial image(5*5) at the accuracy verification phase. Also, the overall accuracy with the consideration of Kappa coefficient were 0.84 for satellite images and 0.82 for aerial images. In all of the images, the smaller training sample was, the higher accuracy showed. Therefore, tree species classification accuracy was tended to rely on training sample size.
 Keywords
Supervised classification;Digital numbers;Satellite imagery;Aerial photography;
 Language
Korean
 Cited by
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