Hyperspectral Imager for the Coastal Ocean: instrument description and first images

Lucke, R. L.; Corson, Michael R.; McGlothlin, N.R.; Butcher, S. D.; Wood, D. L.; Korwan, Daniel; Li, Rong R.; Snyder, W. A.; Davis, C. E.; Chen, Davidson T.

doi:10.1364/ao.50.001501

Cited by 150 publications

(98 citation statements)

References 17 publications

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“…Hyperspectral sensors, e.g., HICO (Lucke et al, 2011), have even more potential in creating algorithms that are specific to particular features in the absorption, fluorescence or backscattering spectra of cyanobacteria. While these algorithms are potentially more accurate for separating cyanobacteria from other types of algae and other substances in the water, they are specific to the band sets of particular sensors (e.g., MERIS).…”

Section: Methods Of Detecting Cyanobacteria Accumulationsmentioning

confidence: 99%

Multidecadal time series of satellite-detected accumulations of cyanobacteria in the Baltic Sea

2014

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Abstract. Cyanobacteria, primarily of the species Nodularia spumigena, form extensive surface accumulations in the Baltic Sea in July and August, ranging from diffuse flakes to dense surface scums. The area of these accumulations can reach ∼ 200 000 km 2 . We describe the compilation of a 35-year-long time series of cyanobacteria surface accumulations in the Baltic Sea using multiple satellite sensors. This appears to be one of the longest satellite-based time series in biological oceanography. The satellite algorithm is based on remote sensing reflectance of the water in the red band, a measure of turbidity. Validation of the satellite algorithm using horizontal transects from a ship of opportunity showed the strongest relationship with phycocyanin fluorescence (an indicator of cyanobacteria), followed by turbidity and then by chlorophyll a fluorescence. The areal fraction with cyanobacteria accumulations (FCA) and the total accumulated area affected (TA) were used to characterize the intensity and extent of the accumulations. The fraction with cyanobacteria accumulations was calculated as the ratio of the number of detected accumulations to the number of cloud-free sea-surface views per pixel during the season (July-August). The total accumulated area affected was calculated by adding the area of pixels where accumulations were detected at least once during the season. The fraction with cyanobacteria accumulations and TA were correlated (R 2 = 0.55) and both showed large interannual and decadalscale variations. The average FCA was significantly higher for the second half of the time series (13.8 %, 1997-2013) than for the first half (8.6 %, 1979-1996). However, that does not seem to represent a long-term trend but decadal-scale oscillations. Cyanobacteria accumulations were common in the 1970s and early 1980s (FCA between 11-17 %), but rare (FCA below 4 %) during 1985-1990; they increased again starting in 1991 and particularly in 1999, reaching maxima in FCA (∼ 25 %) and TA (∼ 210 000 km 2 ) in 2005 and 2008. After 2008, FCA declined to more moderate levels (6-17 %). The timing of the accumulations has become earlier in the season, at a mean rate of 0.6 days per year, resulting in approximately 20 days advancement during the study period. The interannual variations in FCA are positively correlated with the concentration of chlorophyll a during July-August sampled at the depth of ∼ 5 m by a ship of opportunity, but interannual variations in FCA are more pronounced as the coefficient of variation is over 5 times higher.

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Section: Methods Of Detecting Cyanobacteria Accumulationsmentioning

confidence: 99%

Multidecadal time series of satellite-detected accumulations of cyanobacteria in the Baltic Sea

2014

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“…It was configured to collect data spectrally in 160 bands from 273 to 1071 nm at 5 nm spacing, with usable data observed from ~400-900 nm. Pre and postflight spectral, radiometric, and pointing calibrations were performed in the Naval Research Lab (NRL) calibration facility following methods described in [32,33]. MicroSHINE has a 48-degree field of view spread across 1360 cross-track pixels.…”

Section: Visible Airborne Imagery Of the Dyementioning

confidence: 99%

Airborne Remote Sensing of the Upper Ocean Turbulence during CASPER-East

et al. 2018

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This study takes on the challenge of resolving upper ocean surface currents with a suite of airborne remote sensing methodologies, simultaneously imaging the ocean surface in visible, infrared, and microwave bands. A series of flights were conducted over an air-sea interaction supersite established 63 km offshore by a large multi-platform CASPER-East experiment. The supersite was equipped with a range of in situ instruments resolving air-sea interface and underwater properties, of which a bottom-mounted acoustic Doppler current profiler was used extensively in this paper for the purposes of airborne current retrieval validation and interpretation. A series of water-tracing dye releases took place in coordination with aircraft overpasses, enabling dye plume velocimetry over 100 m to 10 km spatial scales. Similar scales were resolved by a Multichannel Synthetic Aperture Radar, which resolved a swath of instantaneous surface velocities (wave and current) with 10 m resolution and 5 cm/s accuracy. Details of the skin temperature variability imprinted by the upper ocean turbulence were revealed in 1-14,000 m range of spatial scales by a mid-wave infrared camera. Combined, these methodologies provide a unique insight into the complex spatial structure of the upper ocean turbulence on a previously under-resolved range of spatial scales from meters to kilometers. However, much attention in this paper is dedicated to quantifying and understanding uncertainties and ambiguities associated with these remote sensing methodologies, especially regarding the smallest resolvable turbulent scales and reference depths of retrieved currents.Keywords: airborne remote sensing; ocean surface currents; upper ocean turbulence BackgroundCapabilities for spatial measurements of ocean surface turbulence are highly desirable for a wide variety of needs ranging from basic studies of upper ocean mixing processes to data assimilation into high-resolution coastal and ocean circulation models. On the global scale, presently available observations of the ocean currents are provided by satellite altimeters, which are limited to mesoscales and resolve only the geostrophic component of the surface current. Much anticipated launches of the

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“…Such discrimination is possible with the Hyperspectral Imager for the Coastal Ocean (HICO) proof-of-concept imaging spectrometer located aboard the International Space Station (21,22). A spectacular HICO image of WLIS on September 23, 2012 captured the water color during the M. rubrum bloom at a resolution of 110 m (Fig.…”

Section: Significancementioning

confidence: 99%

Space station image captures a red tide ciliate bloom at high spectral and spatial resolution

Dierssen

McManus

Chlus

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Mesodinium rubrum is a globally distributed nontoxic ciliate that is known to produce intense red-colored blooms using enslaved chloroplasts from its algal prey. Although frequent enough to have been observed by Darwin, blooms of M. rubrum are notoriously difficult to quantify because M. rubrum can aggregate into massive clouds of rusty-red water in a very short time due to its high growth rates and rapid swimming behavior and can disaggregate just as quickly by vertical or horizontal dispersion. A September 2012 hyperspectral image from the Hyperspectral Imager for the Coastal Ocean sensor aboard the International Space Station captured a dense red tide of M. rubrum (10 6 cells per liter) in surface waters of western Long Island Sound. Genetic data confirmed the identity of the chloroplast as a cryptophyte that was actively photosynthesizing. Microscopy indicated extremely high abundance of its yellow fluorescing signature pigment phycoerythrin. Spectral absorption and fluorescence features were related to ancillary photosynthetic pigments unique to this organism that cannot be observed with traditional satellites. Cell abundance was estimated at a resolution of 100 m using an algorithm based on the distinctive yellow fluorescence of phycoerythrin. Future development of hyperspectral satellites will allow for better enumeration of bloomforming coastal plankton, the associated physical mechanisms, and contributions to marine productivity.

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Hyperspectral Imager for the Coastal Ocean: instrument description and first images

Cited by 150 publications

References 17 publications

Multidecadal time series of satellite-detected accumulations of cyanobacteria in the Baltic Sea

Multidecadal time series of satellite-detected accumulations of cyanobacteria in the Baltic Sea

Airborne Remote Sensing of the Upper Ocean Turbulence during CASPER-East

Space station image captures a red tide ciliate bloom at high spectral and spatial resolution

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