Verification and Validation of Hybridspectral Radiometry Obtained from an Unmanned Surface Vessel (USV) in the Open and Coastal Oceans

Abstract

The hardware and software capabilities of the compact-profiling hybrid instrumentation for radiometry and ecology (C-PHIRE) instruments on an unmanned surface vessel (USV) are evaluated. Both the radiometers and USV are commercial-off-the-shelf (COTS) products, with the latter being only minimally modified to deploy the C-PHIRE instruments. The hybridspectral C-PHIRE instruments consist of an array of 18 multispectral microradiometers with 10 nm wavebands spanning 320–875nm plus a hyperspectral compact grating spectrometer (CGS) with 2048 pixels spanning 190–1000nm. The C-PHIRE data were acquired and processed using two architecturally linked software packages, thereby allowing lessons learned in one to be applied to the other. Using standard data products and unbiased statistics, the C-PHIRE data were validated with those from the well-established compact-optical profiling system (C-OPS) and verified with the marine optical buoy (MOBY). Agreement between algorithm variables used to estimate colored dissolved organic matter (CDOM) absorption and chlorophylla concentration were also validated. Developing and operating novel technologies, such as the C-PHIRE series of instruments , deployed on a USV increase the frequency and coverage of optical observations, which are required to fully support the present and next-generation validation exercises in radiometric remote sensing of aquatic ecosystems.

Extending aquatic spectral information with the first radiometric IR-B field observations

“…To substantiate absolute responsivity in the field across more than one of the three gain stages for all wavebands, observations of celestial targets with known spectral properties are included. Confirming that all wavebands are individually quality assured supports verification ( 28 , 29 ) of IR-A and IR-B observations for targets with substantially unknown spectral properties, including aquatic environments, for which there is presently inadequate validation data that matches the performance of the instruments used herein. The analyzed datasets were obtained opportunistically and constitute an environmental stability gradient spanning illumination conditions (solar to lunar, and clear sky to overcast), variable trophic levels (oligotrophic to eutrophic chlorophyll a , hereafter Chl a , concentrations), and extreme aquatic ecosystems (elevated anthropogenic sources from agricultural chemicals to wildfire ash inputs).…”

“…polarimetry). Hyperspectral sensing increases the number of data products available for extracting information, albeit at the expense of radiometric accuracy ( 29 ) and with high correlation between spectrally adjacent wavebands ( 12 , 44 ). Extraction of polarization information may improve atmospheric correction ( 45 ) and enable new applications ( 46 ).…”

“…Insufficient historical field observations revealing IR-B variability in natural waters ( 20 ) are attributable to in situ instrumentation challenges, in part, because hyperspectral spectrometers—required to support next-generation hyperspectral aquatic science objectives—optimize wavelength resolution at the expense of sampling rate and dynamic range, which degrades sensitivity and spectral range ( 29 ). The IR-B (plus IR-A, UV-B, and UV-A) signals derived herein are not negligible from a next-generation remote sensing perspective, e.g.…”

“…Solar- and lunar-pointing radiometers plus submersible aquatic radiometers are included to establish technological performance metrics and provide verification including AW and IW spectral comparisons for compliant wavebands, e.g. 320–875 nm ( 11 , 12 , 28 , 29 ). Verification is important for two reasons: (a) there is presently inadequate IR-B validation data matching the performance of the instruments used herein; and (b) the celestial radiometry and AW aquatic methods are purely objective and identical for all wavebands, so proven efficacy within the UV-A to IR-A domains is applicable to the IR-B domain.…”

Expanded Signal to Noise Ratio Estimates for Validating Next-Generation Satellite Sensors in Oceanic, Coastal, and Inland Waters

“…For the latter, temporally updated laboratory metadata are combined with unique ancillary sensor records. Briefly, the combination permits preprocessing corrections to reduce uncertainties in data products [35] as follows: (a) time-dependent characterizations; (b) gain-stage transitions; (c) nonreal-time serial timing; (d) illumination geometry and normalizations; (e) planar aperture tilting; and (f) environmental or field characterizations (e.g., dark currents), as appropriate. Intercalibration corrections are not applied, because the absolute calibration of each radiometer is determined independently.…”