Reconstruction of hyperspectral reflectance for optically complex turbid inland lakes: test of a new scheme and implications for inversion algorithms.

Abstract

A new scheme has been proposed by Lee et al. (2014) to reconstruct hyperspectral (400 - 700 nm, 5 nm resolution) remote sensing reflectance (Rrs(λ), sr-1) of representative global waters using measurements at 15 spectral bands. This study tested its applicability to optically complex turbid inland waters in China, where Rrs(λ) are typically much higher than those used in Lee et al. (2014). Strong interdependence of Rrs(λ) between neighboring bands (≤ 10 nm interval) was confirmed, with Pearson correlation coefficient (PCC) mostly above 0.98. The scheme of Lee et al. (2014) for Rrs(λ) re-construction with its original global parameterization worked well with this data set, while new parameterization showed improvement in reducing uncertainties in the reconstructed Rrs(λ). Mean absolute error (MAERrs(λi)) in the reconstructed Rrs(λ) was mostly < 0.0002 sr-1 between 400 and 700nm, and mean relative error (MRERrs(λi)) was < 1% when the comparison was made between reconstructed and measured Rrs(λ) spectra. When Rrs(λ) at the MODIS bands were used to reconstruct the hyperspectral Rrs(λ), MAERrs(λi) was < 0.001 sr-1 and MRERrs(λi) was < 3%. When Rrs(λ) at the MERIS bands were used, MAERrs(λi) in the reconstructed hyperspectral Rrs(λ) was < 0.0004 sr-1 and MRERrs(λi) was < 1%. These results have significant implications for inversion algorithms to retrieve concentrations of phytoplankton pigments (e.g., chlorophyll-a or Chla, and phycocyanin or PC) and total suspended materials (TSM) as well as absorption coefficient of colored dissolved organic matter (CDOM), as some of the algorithms were developed from in situ Rrs(λ) data using spectral bands that may not exist on satellite sensors.