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The Study on Spatial Classification of Riverine Environment using UAV Hyperspectral Image

UAV를 활용한 초분광 영상의 하천공간특성 분류 연구

  • 김영주 (주식회사 자연과기술) ;
  • 한형준 (주식회사 네이처앤휴먼) ;
  • 강준구 (한국건설기술연구원 하천실험센터)
  • Received : 2018.08.10
  • Accepted : 2018.10.05
  • Published : 2018.10.31

Abstract

High-resolution images using remote sensing (RS) is importance to secure for spatial classification depending on the characteristics of the complex and various factors that make up the river environment. The purpose of this study is to evaluate the accuracy of the classification results and to suggest the possibility of applying the high resolution hyperspectral images obtained by using the drone to perform spatial classification. Hyperspectral images obtained from study area were reduced the dimensionality with PCA and MNF transformation to remove effects of noise. Spatial classification was performed by supervised classifications such as MLC(Maximum Likelihood Classification), SVM(Support Vector Machine) and SAM(Spectral Angle Mapping). In overall, the highest classification accuracy was showed when the MLC supervised classification was used by MNF transformed image. However, it was confirmed that the misclassification was mainly found in the boundary of some classes including water body and the shadowing area. The results of this study can be used as basic data for remote sensing using drone and hyperspectral sensor, and it is expected that it can be applied to a wider range of river environments through the development of additional algorithms.

Keywords

Classification;Drone;Hyperspectral image;River environment;UAV

Acknowledgement

Supported by : 한국연구재단

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