Evaluating Distribution Trends of Classification Accuracy by Triangular Training Operator in SAR/VIR FCC : A Case Study of Songkhla Lake Basin in Thailand

SAR/VIR FCC에서 삼각 트레이닝 도구에 의한 분류정확도 분포추세 평가: 태국의 송클라 호수 유역을 사례로

  • Jung Sup Um (Department of Geography, Kyungpook National University)
  • Published : 2003.06.01

Abstract

This study mainly focuses on evaluating how the triangular training operator could improve classification accuracy in SAR(Synthetic Aperture Radar) and VIR FCC(Visible Infra-red, False Colour Composite). The techniques for the determination of the most informative SAR/VIR combinations in the triangular space diagram, as developed tv the author of the paper, are given and the results obtained are presented. The SAR alone, VIR alone and SAR/VIR FCC classification showed trends for gradual improvement of accuracy. Accuracy distribution pattern for individual classes could be explained closely related to SAR/VIR signature components in the process of the triangular synergistic training. Due to contribution of SAR signature in training samples, it was possible to isolate major terrain features such as cloud cover area and roughness target with acceptable spatial precision. It is anticipated that this research output could be used as a valuable reference for distribution trends of classification accuracy obtained by triangular channel space based training in synergistic application.

SAR와 VIR 영상을 디지털 환경에서 통합하여 상승효과를 도출하려는 응용은 아직까지도 탐색적인 연구수준에 머물러 있다. 본 연구는 SAR와 VIR을 통합한 영상에서 삼각 트레이닝 도구가 개별 클라스의 분류 정확도의 분포추세에 미치는 영향을 평가하는 데 주안점을 두고 있다. SAR 데이터와 VIR 데이터가 단일 시너지 영상을 제작하기 위해 통합되었다. 분류정확도의 향상과정이 SAR, VIR, SAR/VIR 통합영상에서 단계적으로 확실하게 도출되었다. 아울러 개별 클라스의 분류정확도가 FCC에 의거한 트레이닝 샘플의 신호(signature)값과 밀접한 상관성을 가지고 분포되는 것이 확인되었다. 한 예로 FCC에서 SAR 영상 신호(signature)의 기여 때문에 구름으로 덮힌 지역과 굴곡을 지닌 지상물체가 (VIR에서는 사실상 분류가 불가능하였던) 상당한 공간 정확도를 가지고 분류되었다. 본 연구가 SAR/VIR을 통합한 응용분야에서 분류정확도의 분포추세에 대한 정량화되고 객관적인 근거가 부재하여 직면하였던 한계를 극복할 수 있는 계기가 되어 향후 SAT/VIR 원격탐사에서 개별 클라스에 대해 확보할 수 있는 분류 정확도에 대한 중요한 참고자료가 될 수 있을 것으로 사료된다.

Keywords

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