• Title/Summary/Keyword: Hypersepcral Image

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The study on Decision Tree method to improve land cover classification accuracy of Hyperspectral Image (초분광영상의 토지피복분류 정확도 향상을 위한 Decision Tree 기법 연구)

  • SEO, Jin-Jae;CHO, Gi-Sung;SONG, Jang-Ki
    • Journal of the Korean Association of Geographic Information Studies
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    • v.21 no.3
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    • pp.205-213
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    • 2018
  • Hyperspectral image is more increasing spectral resolution that Multi-spectral image. Because of that, each pixel of the hyperspectral image includes much more information and it is considered the most appropriate technic for land cover classification. but recent research of hyperspectral image is stayed land cover classification of general level. therefore we classified land cover of detail level using ED, SAM, SSS method and made Decision Tree from result of that. As a result, the overall accuracy of general level was improved by 1.68% and the overall accuracy of detail level was improved by 5.56%.