A global compilation of in situ aquatic high spectral resolution inherent and apparent optical property data for remote sensing applications

Abstract

Abstract. Light emerging from natural water bodies and measured by radiometers contains information about the local type and concentrations of phytoplankton, non-algal particles and colored dissolved organic matter in the underlying waters. An increase in spectral resolution in forthcoming satellite and airborne remote sensing missions is expected to lead to new or improved capabilities for characterizing aquatic ecosystems. Such upcoming missions include NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission; the NASA Surface Biology and Geology designated observable mission; and NASA Airborne Visible/Infrared Imaging Spectrometer – Next Generation (AVIRIS-NG) airborne missions. In anticipation of these missions, we present an organized dataset of geographically diverse, quality-controlled, high spectral resolution inherent and apparent optical property (IOP–AOP) aquatic data. The data are intended to be of use to increase our understanding of aquatic optical properties, to develop aquatic remote sensing data product algorithms, and to perform calibration and validation activities for forthcoming aquatic-focused imaging spectrometry missions. The dataset is comprised of contributions from several investigators and investigating teams collected over a range of geographic areas and water types, including inland waters, estuaries, and oceans. Specific in situ measurements include remote-sensing reflectance, irradiance reflectance, and coefficients describing particulate absorption, particulate attenuation, non-algal particulate absorption, colored dissolved organic matter absorption, phytoplankton absorption, total absorption, total attenuation, particulate backscattering, and total backscattering. The dataset can be downloaded from https://doi.org/10.1594/PANGAEA.902230 (Casey et al., 2019).

Development of a bio-optical model for the Barents Sea to quantitatively link glider and satellite observations

“…Despite best efforts, the combination of no optical profiles in summer and winter Chl levels below detection limits meant that only the four b p spectra collected in the Barents Sea during the spring cruise were available for model development. Comparison with other scattering data collected across a range of Arctic waters in summer and autumn [54] showed, as expected, that chlorophyll and scattering are higher in the Barents Sea in spring, when productivity is at its maximum. Established relationships by Morel et al [57] and Huot et al [58] were compared to the observations.…”

“…One of the limiting factors has been concern over the interpretation of chlorophyll fluorescence signals due to potential issues in manufacturer's calibrations and effects of solar quenching during daylight hours in surface waters. Recent studies have proposed different correction methods for chlorophyll fluorescence measurements, using day/night comparisons, dark measurements at great depth for offset correction or simultaneous PAR measurements for quenching correction, or a combination [54]. Unfortunately, most existing approaches were not applicable for the glider deployments in this study due to the absence of these auxiliary data and day/night patterns.…”

Satellite Remote Sensing of Herring (Clupea pallasii) Spawning Events: A Case Study in the Strait of Georgia

“…Tests over the same types of bright targets from other images showed the same results. Furthermore, when testing over a compiled R rs data set for global waters (Casey et al, 2020) and for inland waters (Sun et al, 2015), there is nearly no exception that all these waters have their SAM values >5° if referenced against the herring spawn R rs spectra (Figures 3b and 3c), further proving the unique spectral shape between 490 and 560 nm from herring spawning waters. The same test using MSI bands of 490 and 560 nm also confirmed this observation (Figure S3), as nonspawn bright pixels from shallow waters, inter-tidal zone, and suspended sediments in the SoG all showed different spectral shapes (relatively large SAM values) from herring spawn pixels.…”

Hyperspectral reflectance spectra of floating matters derived from Hyperspectral Imager for the Coastal Ocean (HICO) observations

“…From such derived spectra, a secondary objective is to analyze whether they can be differentiated spectrally. Similarly to the compiled hyperspectral dataset for inherent and apparent optical properties to support future hyperspectral missions such as NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission (Casey et al, 2020), such a dataset for floating matters is expected to help develop or improve algorithms for the PACE mission as well as for the hyperspectral Surface Biology and Geology (SBG) mission currently being planned by NASA (Cawse-Nicholson et al, 2021).…”