The feasibility of using remote-sensing data with high spatial resolution was assessed for monitoring and modelling of chlorophyll-a (chl-a) in river waters. Two-band and three-band reflectance models including the red-edge band were examined as spectral coefficients using
a RapidEye image for river waters, where the scale is smaller and narrower than for ocean waters. A red‐red-edge‐NIR three-band model calculated by a cubic function explained 73% of variance in the estimated data using the relationship between spectral indices such as absorption
coefficients obtained using the model and chl-a concentrations and performed better than the red‐red-edge two-band. Chl-a concentrations were simulated by a one-dimensional water quality model, QUALKO2, and image-derived and measured chl-a concentrations were applied
in the calibration step of simulation. The image-derived chl-a dataset showed more stable calibration throughout the study area and enhanced the results rather than measured data. It is expected that chl-a estimation techniques using high resolution satellite data, RapidEye,
have the capability to support rapid and widespread water quality monitoring and modelling, when a field dataset is not large or precise enough to do it, but still requires the improvement of estimation accuracy.
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Document Type: Research Article
Monitoring and Analysis Division, Nakdong River Basin Environmental Office, Changwon-si, Gyeongsangnam-do, 641-722, Republic of Korea
Nakdong River Environment Research Centre, National Institute of Environmental Research (NIER), Goryeong-gun, Gyeongsangbuk-do, 717-873, Republic of Korea
Publication date: March 19, 2015
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