Nimbus-7 Coastal Zone Color Scanner: System Description and Initial Imagery

Hovis, W. A.; Clark, Dennis; Anderson, F.P.; Austin, R. W.; Wilson, Wayne H.; Baker, Edward T.; Ball, D. F.; Gordon, Howard R.; Mueller, James L.; El‐Sayed, Sayed Z.; Sturm, B.; Wrigley, R. C.; Yentsch, Charles S.

doi:10.1126/science.210.4465.60

Cited by 337 publications

(109 citation statements)

References 14 publications

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“…For the estimation of pigment biomass, satellite observations of ocean color have been used now for over two decades (Smith and Baker, 1978;Gordon and Morel, 1983;Hovis et al, 1980). Basically, the spectral reflectance (or ocean ''color'') is determined by the backscattering and absorption of the dissolved and suspended materials within the upper layers of the water column.…”

Section: Pigment Biomassmentioning

confidence: 99%

Variability of Primary Production in an Antarctic Marine Ecosystem as Estimated Using a Multi-scale Sampling Strategy

Smith¹,

Baker²,

Dierssen³

et al. 2001

Am Zool

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SYNOPSIS. A major objective of the multidisciplinary Palmer Long Term Ecological Research (LTER)program is to obtain a comprehensive understanding of various components of the Antarctic marine ecosystem-the assemblage of plants, animals, ocean, sea ice, and island components south of the Antarctic Convergence. Phytoplankton production plays a key role in this polar ecosystem, and factors that regulate production include those that control cell growth (light, temperature, nutrients) and those that control cell accumulation rate and hence population growth (water column stability, advection, grazing, and sinking). Several of these factors are mediated by the annual advance and retreat of sea ice. In this study, we examine the results from nearly a decade (1991-2000) of ecological research in the western Antarctic Peninsula region. We evaluate the spatial and temporal variability of phytoplankton biomass (estimated as chlorophyll-a concentration) and primary production (determined in-situ aboard ship as well as estimated from ocean color satellite data). We also present the spatial and temporal variability of sea ice extent (estimated from passive microwave satellite data). While the data record is relatively short from a long-term perspective, evidence is accumulating that statistically links the variability in sea ice to the variability in primary production. Even though this marine ecosystem displays extreme interannual variability in both phytoplankton biomass and primary production, persistent spatial patterns have been observed over the many years of study (e.g., an on to offshore gradient in biomass and a growing season characterized by episodic phytoplankton blooms). This high interannual variability at the base of the food chain influences organisms at all trophic levels.

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Section: Pigment Biomassmentioning

confidence: 99%

Variability of Primary Production in an Antarctic Marine Ecosystem as Estimated Using a Multi-scale Sampling Strategy

Smith¹,

Baker²,

Dierssen³

et al. 2001

Am Zool

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“…the so-called patchiness problem. The availability of data obtained by the Coastal Zone Color Scanner (CZCS) onboard the Nimbus-7 satellite (Austin 1980;Hovis et al 1980) has greatly increased the possibilities of analyzing the patterns of distribution of phytoplankton pigments, both in space and in time (Smith and Baker 1982;Gordon et al 1983). Here, we use a 34-month CZCS data set, available at the Scripps Satellite-Oceanography Facility, to describe the major phytoplankton pigment patterns in the California Current in time and space.…”

Section: The Californiamentioning

confidence: 99%

Phytoplankton pigment patterns in the California Current as determined by satellite1

Peláez

McGowan

1986

Limnology & Oceanography

150

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The satellite images of phytoplankton pigments off California show a high degree of heterogeneity. However, recurrent phytoplankton pigment structures can be identified in the California Current. The major ones are: two sharp boundaries several hundreds of kilometers long; low pigment eddies far offshore interwoven with higher pigment structures immediately inshore; a low pigment intrusion in the Southern California Bight, and a higher pigment region farther offshore; eddies "attached" to shallow coastal areas; and California Current rings spawned far offshore.The larger scale structures of phytoplankton pigments show a remarkable continuity throughout a year, but there is shifting, wobbling, and erosion of these structures. The structures are strong and distinct in spring and summer, weaken through fall (except for a slight intensification in October), and become weakest and poorly defined in late fall-early winter. The patterns of distribution of phytoplankton pigments for a given season tend to reappear from one year to another in the 3 years analyzed. Such recurrency is significant because these patterns may change, and some disappear, within any given year.Clear similarities of the phytoplankton pigment distributions to the field of dynamic height and to an infrared image of sea surface temperature indicate the very important role of ocean circulation, and of phytoplankton nutrient content of the waters, in the generation and maintenance of the observed patterns.

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“…Since the launch of the Coast Zone Color Scanner in 1978 (Gordon et al 1980;Hovis et al 1980), satellite oceancolor remote sensing has been mostly focusing on the visible wavelengths (i.e., ocean color). A variety of satellite ocean-color algorithms that use normalized water-leaving radiance spectra nL w (l) in the blue and green wavelengths for retrieval of ocean parameters such as chlorophyll a (Chl a), water diffuse attenuation coefficient at the wavelength of 490 nm K d (490), colored dissolved organic matter (CDOM), calcium particulate inorganic carbon (PIC), and ocean's inherent optical properties (IOPs) have been developed, evaluated, and validated.…”

mentioning

confidence: 99%

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

Shi

Wang

2014

Limnology & Oceanography

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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.

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Nimbus-7 Coastal Zone Color Scanner: System Description and Initial Imagery

Cited by 337 publications

References 14 publications

Variability of Primary Production in an Antarctic Marine Ecosystem as Estimated Using a Multi-scale Sampling Strategy

Variability of Primary Production in an Antarctic Marine Ecosystem as Estimated Using a Multi-scale Sampling Strategy

Phytoplankton pigment patterns in the California Current as determined by satellite1

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

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