研究目的
Development and validation of the surface suspended sediment concentration (SSC) models derived from the surface remote-sensing reflectance spectra [Rrs (λ)] for satellite monitoring of estuarine and coastal waters.
研究成果
Empirical models are generally superior to the semianalytical models for solution existence, prediction accuracy, and correlation with the observed SSC values. However, all semianalytical models using the red to green spectral ratio have demonstrated approximately the same accuracy and correlation as empirical models, providing an additional support for using more simple easily calculated empirical models.
研究不足
The success of SSC versus Rrs(λ) empirical models depends strongly on environmental conditions, for which the initial model was applied. The degree of temporal variability of the waters under consideration is high, affecting the accuracy of both empirical and semianalytical models.
1：Experimental Design and Method Selection:
Comparison of seven empirical and seven semianalytical spectral reflectance models for evaluation of the surface SSC with laboratory tank and in situ measurements performed in different natural waters of East China.
2：Sample Selection and Data Sources:
Three databases of SSC and reflectance spectra data were used: laboratory measurements in tanks carried out in July 2006, in situ measurements carried out in May 2011 and February–March 2014 in the delta of the Yangtze River and the coastal zone of the East China Sea.
3：List of Experimental Equipment and Materials:
Satlantic, Inc.’s Hyperspectral Surface Acquisition System (HyperSAS) for radiance measurements.
4：Experimental Procedures and Operational Workflow:
Conversions of measured radiometric spectra to Rrs(λ) were performed by the Mobley and Saunderson—Aas models for laboratory and in situ measurements, respectively.
5：Data Analysis Methods:
Statistical analysis to find the best models and spectral ratios for remote-sensing monitoring purposes.
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