Journal of Korean Society on Water Environment (한국물환경학회지)

Korean Society on Water Environment (한국물환경학회)
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Estimating Chlorophyll-a Concentration using Spectral Mixture Analysis from RapidEye Imagery in Nak-dong River Basin

RapidEye영상과 선형분광혼합화소분석 기법을 이용한 낙동강 유역의 클로로필-a 농도 추정

  • Lee, Hyuk (Water Quality Assessment Research Division, National Institute of Environmental Research) ;
  • Nam, Gibeom (Water Quality Assessment Research Division, National Institute of Environmental Research) ;
  • Kang, Taegu (Water Quality Assessment Research Division, National Institute of Environmental Research) ;
  • Yoon, Seungjoon (Korean Environmental Industry and Technology Institute)
  • 이혁 (국립환경과학원 물환경평가연구과) ;
  • 남기범 (국립환경과학원 물환경평가연구과) ;
  • 강태구 (국립환경과학원 물환경평가연구과) ;
  • 윤승준 (한국환경산업기술원)
  • Received : 2013.12.17
  • Accepted : 2014.05.19
  • Published : 2014.05.30
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Abstract

This study aims to estimate chlorophyll-a concentration in rivers using multi-spectral RapidEye imagery and Spectral Mixture Analysis (SMA) and assess the applicability of SMA for multi-temporal imagery analysis. Comparison between images (acquired on Oct. and Nov., 2013) predicted and ground reference chlorophyll-a concentration showed significant performance statistically with determination coefficients of 0.49 and 0.51, respectively. Two band (Red-RE) model for the October and November 2013 RapidEye images showed low performance with coefficient of determinations ($R^2$) of 0.26 and 0.16, respectively. Also Three band (Red-RE-NIR) model showed different performance with $R^2$ of 0.016 and 0.304, respectively. SMA derived Chlorophyll-a concentrations showed relatively higher accuracy than band ratio models based values. SMA was the most appropriate method to calculate Chlorophyll-a concentration using images which were acquired on period of low Chlorophyll-a concentrations. The results of SMA for multi-temporal imagery showed low performance because of the spatio-temporal variation of each end members. This approach provides the potential of providing a cost effective method of monitoring river water quality and management using multi-spectral imagery. In addition, the calculated Chlorophyll-a concentrations using multi-spectral RapidEye imagery can be applied to water quality modeling, enhancing the predicting accuracy.

Keywords

References

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