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Estimation of Colored Dissolved Organic Matter From Landsat-8 Imagery for Complex Inland Water: Case Study of Lake Huron
Spectral reflectance data, including irradiance reflectance (R_{t}) and remote sensing reflectance (R_{\mathrm {rs}} , sr ^{-1}) , and colored dissolved organic matter (CDOM) absorption coefficients a_{\mathrm {CDOM}} (440), were collected in the Saginaw River and Kawkawlin River plume regions of Lake Huron. We developed an empirical band ratio algorithm to derive a_{\mathrm {CDOM}} (440) that could be directly applicable to Landsat-8 imagery. A model ranking method is used to determine the best band ratios as well as their empirical functions. One problem of previous CDOM estimations from Landsat imagery is that they usually use R_{t} or R_{t}/\pi rather than the real R_{\mathrm {rs}} as the input data, but as a result of our study, algorithms derived using R_{\mathrm {rs}} performed much better than using R_{t} . The green/red band ratio gave the best accuracies by fitting with power and exponential models (power model: R^{{2}} = 0.819 and RMSE =0.889~\text{m}^{-1} and exponential model: R^{2} = 0.829 and RMSE =0.863~\text{m}^{-1}) . The power and exponential models were further validated using an independent data group, achieving excellent results with the RMSE of 0.642 and 0.504 \text{m}^{-1} , respectively. The application of the exponential model a_{\mathrm {CDOM}} (440) = 40.75e −2.463 x , x = R_{\mathrm {rs}} (B3)/ R_{\mathrm {rs}} (B4) on two Landsat-8 images demonstrated that estimating CDOM from to Landsat-8 imagery has potential applications for monitoring water quality in long term and large scale.
Estimation of Colored Dissolved Organic Matter From Landsat-8 Imagery for Complex Inland Water: Case Study of Lake Huron
Spectral reflectance data, including irradiance reflectance (R_{t}) and remote sensing reflectance (R_{\mathrm {rs}} , sr ^{-1}) , and colored dissolved organic matter (CDOM) absorption coefficients a_{\mathrm {CDOM}} (440), were collected in the Saginaw River and Kawkawlin River plume regions of Lake Huron. We developed an empirical band ratio algorithm to derive a_{\mathrm {CDOM}} (440) that could be directly applicable to Landsat-8 imagery. A model ranking method is used to determine the best band ratios as well as their empirical functions. One problem of previous CDOM estimations from Landsat imagery is that they usually use R_{t} or R_{t}/\pi rather than the real R_{\mathrm {rs}} as the input data, but as a result of our study, algorithms derived using R_{\mathrm {rs}} performed much better than using R_{t} . The green/red band ratio gave the best accuracies by fitting with power and exponential models (power model: R^{{2}} = 0.819 and RMSE =0.889~\text{m}^{-1} and exponential model: R^{2} = 0.829 and RMSE =0.863~\text{m}^{-1}) . The power and exponential models were further validated using an independent data group, achieving excellent results with the RMSE of 0.642 and 0.504 \text{m}^{-1} , respectively. The application of the exponential model a_{\mathrm {CDOM}} (440) = 40.75e −2.463 x , x = R_{\mathrm {rs}} (B3)/ R_{\mathrm {rs}} (B4) on two Landsat-8 images demonstrated that estimating CDOM from to Landsat-8 imagery has potential applications for monitoring water quality in long term and large scale.
Estimation of Colored Dissolved Organic Matter From Landsat-8 Imagery for Complex Inland Water: Case Study of Lake Huron
Chen, Jiang (author) / Zhu, Wei-Ning / Tian, Yong Q / Yu, Qian
2017
Article (Journal)
English
Local classification TIB:
770/3710/5670
BKL:
38.03
Methoden und Techniken der Geowissenschaften
/
74.41
Luftaufnahmen, Photogrammetrie
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