Ocean reflectance spectra at the red, near‐infrared, and shortwave infrared from highly turbid waters: A study in the Bohai Sea, Yellow Sea, and East China Sea

Abstract

Normalized water-leaving radiance spectra nL w (l) at the red, near-infrared (NIR), and shortwave infrared (SWIR) are quantified and characterized in highly turbid waters of the western Pacific using 3 yr (2009)(2010)(2011) observations from the Moderate Resolution Imaging Spectroradiometer on the satellite Aqua. nL w (645; red), nL w (859; NIR), and nL w (1240; SWIR) were higher in the coastal region and river estuaries, with SWIR nL w (1240) reaching up to , 0.2 mW cm 22 mm 21 sr 21 in Hangzhou Bay during winter. The NIR ocean-reflectance spectral shape represented by the ratio of the normalized water-leaving reflectance r wN (l) at the two NIR bands r wN (748) : r wN (869) is highly dynamic and region-dependent. The NIR spectral feature associated with the sediment source from the Yellow River and Ancient Yellow River is noticeably different from that of the Yangtze River. There are non-negligible SWIR nL w (1240) contributions for waters with the NIR nL w (859) . , 2.5 mW cm 22 mm 21 sr 21 . Estimation of the NIR ocean reflectance with iterative approaches might only be accurate for turbid waters with nL w (859) , , 1.5 mW cm 22 mm 21 sr 21 . Thus, the SWIR atmospherics correction algorithm for satellite ocean-color data processing is indispensable to derive accurate nL w (l) for highly turbid waters. Current existing satellite algorithms for chlorophyll a, diffuse attenuation coefficient at the wavelength of 490 nm (K d (490)), total suspended matter, and inherent optical properties (IOPs) using nL w (l) at the red band for coastal waters are limited and can only be applied to turbid waters with nL w (859) , , 1.5 mW cm 22 mm 21 sr 21 . Thus, the NIR nL w (l) measurements are required to characterize water properties for highly turbid waters. Based on the fact that pure water absorption is significantly larger than other absorption components in the NIR wavelengths, we show that it is feasible to analytically derive accurate IOP data for turbid waters with combined satellite-measured visible-NIR nL w (l) spectra data.

Evaluation of MODIS-Aqua Atmospheric Correction and Chlorophyll Products of Western North American Coastal Waters Based on 13 Years of Data

“…A few factors contribute to the observed uncertainties. High turbidity levels in the Salish Sea may cause non-negligible R rs (1240 nm), thus resulting in poor aerosol product retrievals, as it has been reported for other turbid waters [56][57][58]. Turbidity in the Salish Sea reaches values around 30.0 mg L −1 in waters under high influence of the Fraser River plume [16,39].…”

“…While there exists a MODIS 1640 nm band with improved SNR compared to the 1240 nm band (495 vs. 157 on-orbit measured, respectively [61]), it is currently non-functional due to a number of broken detectors [62]. Although the current 1240 and 2130 nm SWIR bands have produced effective results in some regions with turbid waters [57,63], other studies, similar to our results, show that the lower SNR often produces poor outcomes [62,64,65]. Specific to our results, this lower SNR resulted in the largest uncertainties and overall variability of MODIS τ a when compared with AERONET, and ultimately inaccurate chlorophyll products (Table 4).…”

Remote Sensing of Spatiotemporal Variation of Apparent Optical Properties in Bohai Sea

“…Many studies have been carried out on the remote sensing of optical properties of Bohai sea. Taking Bohai sea as an example, the water reflectance in the wavelengths of red, near-infrared (NIR), and shortwave infrared (SWIR) were studied [4]. A semianalytical model was established for retrieving the attenuation coefficients from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery [5].…”

Sensor Capability and Atmospheric Correction in Ocean Colour Remote Sensing

“…However, turbid waters are a complex mix of constituents, such as phytoplankton, CDOM and suspended particulate matter (SPM). Constituent retrieval algorithms for these waters need to make use of reflectance values in the red and NIR parts of the spectrum, as these regions are less affected by CDOM and SPM [114,215]. Although the majority of constituent retrieval algorithms for turbid waters have been developed for multispectral sensors and their estimates of chlorophyll-a are poor [25], a recent method has shown some success at retrieving the chlorophyll-a concentration in turbid waters [251].…”

“…The SWIR approach has fundamentally resolved the black pixel assumption issue for atmospheric correction over turbid coastal and inland waters [29]. In fact, the SWIR-based atmospheric correction algorithm has been successfully used for accurately deriving ocean colour products over highly turbid coastal and inland waters for various applications [9,10,33,[210][211][212][213][214][215][216]. However, the low SNR in the SWIR bands is a major limitation [203].…”