Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4398750 | Journal of Great Lakes Research | 2013 | 14 Pages |
Abstract
Observations of remote sensing reflectance (Rrs), the signal available to support remote sensing of optically active constituents (OACs) of water quality interest, are presented for multiple sites within each of the Laurentian Great Lakes based on in situ measurements made with a hyperspectral radiometer. Rrs(λ) spectra are contrasted among these lakes and in time and space within selected systems. Qualitative analyses of spectra are provided that identify the inherent optical property (IOP) and coupled OAC conditions responsible for the differences in Rrs(λ). The much higher Rrs peaks observed in the green wavelengths for the lower Great Lakes (Erie and Ontario) are attributed to elevated backscattering levels caused by higher concentrations of minerogenic particles. The credibility of the Rrs(λ) spectra is established through successful closure analyses that demonstrate good matches with IOP-based predictions and consistency of coefficient values for radiative transfer expressions with related literature and theory. A mechanistic forward model of Rrs(λ) is developed that accommodates the effects of three OACs, including metrics of phytoplankton biomass, minerogenic particles and colored dissolved organic material. This includes the development of the critical cross-section relationships that quantify the couplings between the OACs and IOPs, and in turn the IOPs and the Rrs(λ) signal. The model is demonstrated to perform well in matching observations in Lake Erie, and to be sensitive to the representation of the spectral dependency of backscattering and likely variations in the dependence of phytoplankton absorption on chlorophyll. The modeled predicted responses of Lake Erie to different OAC levels are presented.
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Earth and Planetary Sciences (General)
Authors
David M. O'Donnell, Steven W. Effler, Christopher M. Strait, Feng Peng, MaryGail Perkins,