Observation of chlorophyll fluorescence in west coast waters of Canada using the MODIS satellite sensor

Gower, J. F. R.; Brown, Leslie; Borstad, Gary A.

doi:10.5589/m03-048

Cited by 86 publications

(61 citation statements)

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“…9). We also show a comparison with the model of Gower et al (2004), which is based on average values of measured fluorescence emission scaled to irradiance for the sun at zenith (middle Fig. 9, dashed black line).…”

Section: Comparing the Finite-depth Modis Algorithm To A Complete Depmentioning

confidence: 99%

“…Their model follows the central trends of the MODIS data in this region. Part of the variability in the top and middle panels is due to variability in the quantum yield of fluorescence, the chlorophyll-specific absorption coefficient, the error in the determination of chlorophyll from band ratios, and the striping due to detector-to-detector calibration observed in MODIS images (Gower et al 2004;Salomonson 2004). It should also be kept in mind that the depths sampled by the ocean color and fluorescence techniques are different and become more similar as chlorophyll concentration increases.…”

Section: Comparing the Finite-depth Modis Algorithm To A Complete Depmentioning

confidence: 99%

“…MODIS measures the upwelling radiance at 676.7 nm (bandwidth 673 to 683 nm, henceforth referred to as the 678 nm waveband), whereas the maximum emission of fluorescence is around 683 to 685 nm. This offset was chosen to avoid an atmospheric oxygen absorption band at 687 nm (Letelier and Abbott 1996;Abbott and Letelier 1999;Gower et al 2004). In addition to reducing the sensitivity, the offset places the measurement closer to the absorption peak at 676 nm for chlorophyll a in vivo, and consequently, measured fluorescence can be reduced by up to 40% by intracellular reabsorption.…”

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confidence: 99%

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New algorithms for MODIS sun-induced chlorophyll fluorescence and a comparison with present data products

Huot

Brown

Cullen

2005

Limnol. Oceanogr. Methods

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The launch of the MODIS instrument (Esaias et al. 1998), with a waveband dedicated to the measurement of sun-induced chlorophyll fluorescence, has taken remote sensing of marine phytoplankton in a new direction. In theory, it is now possible to obtain a global quasi-synoptic assessment of near-surface fluorescence emission and its quantum yield. While the remote measurement of in vivo fluorescence emitted by phytoplankton is, in principle, straightforward (but see Letelier and Abbott 1996), obtaining an estimate of the quantum yield of fluorescence (the ratio of fluoresced to absorbed photons by phytoplankton) requires a complex algorithm (Abbott and Letelier 1999). Yet, this physiological measurement could foster a major leap in our understanding of the ocean by providing global coverage of a parameter linked to algal physiology (Kiefer and Reynolds 1992) and species composition (Loftus and Seliger 1975;Heaney 1978). In this study, we review the sources of variability of sun-induced fluorescence as they affect the MODIS data products and examine how they relate to the retrieval of the quantum yield of fluorescence and chlorophyll concentration. We propose new algorithms based on semi-empirical relationships from the bio-optical literature and compare our results to MODIS data products.Nature of the MODIS fluorescence measurement-Quantum yield of chlorophyll fluorescence. In this study, we define the quantum yield of chlorophyll a fluorescence in vivo (ϕ, dimensionless; see Table 1 for symbols and definitions) as the ratio of photons fluoresced by chlorophyll a over the whole fluorescence band to the photons absorbed by all cellular pigments. Others have referred to this as the apparent quantum yield of chlorophyll a fluorescence, limiting the term quantum yield of chlorophyll a fluorescence to the ratio of photons fluoresced by chlorophyll a (or by chlorophyll a associated with photosystem II [PSII]) to those absorbed only by photosynthetic pigments associated with PSII (e.g., Gilmore and Govindjee 1999). This distinction is important for the physiological interpretation of remote sensing data and for the comparison with laboratory measurements (see Web Appendix 2). New algorithms for MODIS sun-induced chlorophyll fluorescence and a comparison with present data products AbstractWe discuss important sources of variability in sun-induced chlorophyll fluorescence and examine difficulties in deriving fluorescence data products from satellite imagery, with a focus on the MODerate-resolution Imaging Spectroradiometer (MODIS) sensor. Our results indicate that there are limitations in the present MODIS algorithms that could lead to biases in the interpretation of the fluorescence products across gradients of chlorophyll concentration. To avoid some of these limitations, we suggest replacing the calculation of absorbed radiation by phytoplankton (ARP) over a finite depth with integration over the entire water column, and including a term accounting for cellular reabsorption of fluoresced light. These suggestions are in...

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Section: Comparing the Finite-depth Modis Algorithm To A Complete Depmentioning

confidence: 99%

Section: Comparing the Finite-depth Modis Algorithm To A Complete Depmentioning

confidence: 99%

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confidence: 99%

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New algorithms for MODIS sun-induced chlorophyll fluorescence and a comparison with present data products

Huot

Brown

Cullen

2005

Limnol. Oceanogr. Methods

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“…The bottom reflectance affects the entire water column, and is treated properly with IOPs along the depth (Lee et al, 1998). The source function based on the chlorophyll is included in the model and its effect is clearly seen in the simulated E u and L u with a florescence peak at 0.685 µm (Gower et al, 2004). Finally, the calculated transmittance T (z) is purely based on the IOPs (Haltrin and Kattawar, 1993;Haltrin, 1998a, b) and the reflectance R(z) based on the IOPs and bottom effects (Lee et al, 1998).…”

Section: Discussionmentioning

confidence: 99%

Modelling of underwater light fields in turbid and eutrophic waters: application and validation with experimental data

Sundarabalan

Shanmugam

2015

Ocean Sci.

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Abstract.A reliable radiative transfer (RT) model is an essential and indispensable tool for understanding the radiative transfer processes in homogenous and layered waters, analyzing measurements made by radiance sensors and developing remote-sensing algorithms to derive meaningful physical quantities and biogeochemical variables in turbid and productive coastal waters. Existing radiative transfer models have been designed to be applicable to either homogenous waters or inhomogeneous waters. To overcome such constraints associated with these models, this study presents a radiative transfer model that treats a homogenous layer as a diffuse part and an inhomogeneous layer as a direct part in the water column and combines these two parts appropriately in order to generate more reliable underwater lightfield data such as upwelling radiance (L u ), downwelling irradiance (E d ) and upwelling irradiance (E u ). The diffuse model assumes the inherent optical properties (IOPs) to be vertically continuous and the light fields to exponentially decrease with depth, whereas the direct part considers the water column to be vertically inhomogeneous (layer-by-layer phenomena) with the vertically varying phase function. The surface and bottom boundary conditions, source function due to chlorophyll and solar incident geometry are also included in the present RT model. The performance of this model is assessed in a variety of waters (clear, turbid and eutrophic) using the measured radiometric data. The present model shows an advantage in terms of producing accurate L u , E d and E u profiles (in spatial domain) in different waters determined by both homogenous and inhomogeneous conditions. The feasibility of predicting these underwater light fields based on the remotely estimated IOP data is also examined using the present RT model. For this application, vertical profiles of the water constituents and IOPs are estimated by empirical models based on our in situ data. The present RT model generates L u , E d and E u spectra closely consistent with the measured data. These results lead to a conclusion that the present RT model is a viable alternative to existing RT models and has an important implication for remote sensing of optically complex waters.

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“…This type of approach could be particularly useful in a complex system such as the Danube basin and the Black Sea where multi-sensor approaches seem to be required to handle the variable scale of its component waters. While the removal of the atmosphere from the total signal measured by a space-borne sensor is still considered challenging over inland and near-shore waters, in turbid systems with high signal-to-noise some algorithms can compute water biogeochemical properties successfully from top-ofatmosphere radiances (Gower et al, 2004) or Rayleigh-corrected reflectances (Matthews et al, 2012).…”

Section: Constituent Retrievalmentioning

confidence: 99%

Developments in Earth observation for the assessment and monitoring of inland, transitional, coastal and shelf-sea waters

Tyler

Hunter

Spyrakos

et al. 2016

Science of The Total Environment

130

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The Earth's surface waters are a fundamental resource and encompass a broad range of ecosystems that are core to global biogeochemical cycling and food and energy production.Despite this, the Earth's surface waters are impacted by multiple natural and anthropogenic pressures and drivers of environmental change. The complex interaction between physical, chemical and biological processes in surface waters poses significant challenges for in situ monitoring and assessment and often limits our ability to adequately capture the dynamics of aquatic systems and our understanding of their status, functioning and response to pressures. Here we explore the opportunities that Earth observation (EO) has to offer to basin-scale monitoring of water quality over the surface water continuum comprising inland, transition and coastal water bodies, with a particular focus on the Danube and Black Sea region. This review summarises the technological advances in EO and the opportunities that the next generation satellites offer for water quality monitoring. We provide an overview of algorithms for the retrieval of water quality parameters and demonstrate how such models have been used for the assessment and monitoring of inland, transitional, coastal and shelfsea systems. Further, we argue that very few studies have investigated the connectivity between these systems especially in large river-sea systems such as the Danube-Black Sea. Subsequently, we describe current capability in operational processing of archive and near real-time satellite data. We conclude that while the operational use of satellites for the assessment and monitoring of surface waters is still developing for inland and coastal waters and more work is required on the development and validation of remote sensing algorithms for these optically complex waters, the potential that these data streams offer for developing an improved, potentially paradigm-shifting understanding of physical and biogeochemical processes across large scale river-sea continuum including the Danube-Black Sea is considerable.

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Observation of chlorophyll fluorescence in west coast waters of Canada using the MODIS satellite sensor

Cited by 86 publications

References 4 publications

New algorithms for MODIS sun-induced chlorophyll fluorescence and a comparison with present data products

New algorithms for MODIS sun-induced chlorophyll fluorescence and a comparison with present data products

Modelling of underwater light fields in turbid and eutrophic waters: application and validation with experimental data

Developments in Earth observation for the assessment and monitoring of inland, transitional, coastal and shelf-sea waters

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