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Coupling remote sensing with computational fluid dynamics modelling to estimate lake chlorophyll-a concentration

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Coupling remote sensing with computational fluid dynamics modelling to estimate lake chlorophyll-a concentration. / Hedger, Richard; Olsen, Nils R. B.; Malthus, Tim J. et al.
In: Remote Sensing of Environment, Vol. 79, No. 1, 01.2002, p. 116-122.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Hedger R, Olsen NRB, Malthus TJ, Atkinson PM. Coupling remote sensing with computational fluid dynamics modelling to estimate lake chlorophyll-a concentration. Remote Sensing of Environment. 2002 Jan;79(1):116-122. Epub 2001 Dec 11. doi: 10.1016/S0034-4257(01)00244-9

Author

Hedger, Richard ; Olsen, Nils R. B. ; Malthus, Tim J. et al. / Coupling remote sensing with computational fluid dynamics modelling to estimate lake chlorophyll-a concentration. In: Remote Sensing of Environment. 2002 ; Vol. 79, No. 1. pp. 116-122.

Bibtex

@article{887d97127f4b45df9dbd54edd9587f73,
title = "Coupling remote sensing with computational fluid dynamics modelling to estimate lake chlorophyll-a concentration",
abstract = "A remotely sensed image of Loch Leven, a shallow meso-eutrophic lake in Central East Scotland, UK, revealed a strong gradient in chlorophyll-a (chl-a) concentration. As a means of interpreting the spatial distribution of chl-a in this image, a combined three-dimensional computational fluid dynamics (CFD) and ecological model was run using estimates of the environmental and planktonic conditions concurrent with and preceding the time of image acquisition. The post facto modelling of the dynamics of the lake produced spatial distributions of surface chl-a that were consistent with that evident in the remotely sensed image. It is proposed that CFD modelling benefits the interpretation of remotely sensed images of water bodies in that it may be used to infer the causes of the spatial distributions evident in the remotely sensed imagery. This is because modelling extends the analysis into the temporal and vertical domains. However, the value of combining CFD with remote sensing is limited by the quality and quantity of data available through surface observation and remote sensing, and the implications of this to the integration of CFD with remote sensing are discussed.",
keywords = "Computational fluid dynamics, Phytoplankton, Chlorophyll index, Loch Leven",
author = "Richard Hedger and Olsen, {Nils R. B.} and Malthus, {Tim J.} and Atkinson, {Peter M.}",
note = "M1 - 1",
year = "2002",
month = jan,
doi = "10.1016/S0034-4257(01)00244-9",
language = "English",
volume = "79",
pages = "116--122",
journal = "Remote Sensing of Environment",
issn = "0034-4257",
publisher = "Elsevier Inc.",
number = "1",

}

RIS

TY - JOUR

T1 - Coupling remote sensing with computational fluid dynamics modelling to estimate lake chlorophyll-a concentration

AU - Hedger, Richard

AU - Olsen, Nils R. B.

AU - Malthus, Tim J.

AU - Atkinson, Peter M.

N1 - M1 - 1

PY - 2002/1

Y1 - 2002/1

N2 - A remotely sensed image of Loch Leven, a shallow meso-eutrophic lake in Central East Scotland, UK, revealed a strong gradient in chlorophyll-a (chl-a) concentration. As a means of interpreting the spatial distribution of chl-a in this image, a combined three-dimensional computational fluid dynamics (CFD) and ecological model was run using estimates of the environmental and planktonic conditions concurrent with and preceding the time of image acquisition. The post facto modelling of the dynamics of the lake produced spatial distributions of surface chl-a that were consistent with that evident in the remotely sensed image. It is proposed that CFD modelling benefits the interpretation of remotely sensed images of water bodies in that it may be used to infer the causes of the spatial distributions evident in the remotely sensed imagery. This is because modelling extends the analysis into the temporal and vertical domains. However, the value of combining CFD with remote sensing is limited by the quality and quantity of data available through surface observation and remote sensing, and the implications of this to the integration of CFD with remote sensing are discussed.

AB - A remotely sensed image of Loch Leven, a shallow meso-eutrophic lake in Central East Scotland, UK, revealed a strong gradient in chlorophyll-a (chl-a) concentration. As a means of interpreting the spatial distribution of chl-a in this image, a combined three-dimensional computational fluid dynamics (CFD) and ecological model was run using estimates of the environmental and planktonic conditions concurrent with and preceding the time of image acquisition. The post facto modelling of the dynamics of the lake produced spatial distributions of surface chl-a that were consistent with that evident in the remotely sensed image. It is proposed that CFD modelling benefits the interpretation of remotely sensed images of water bodies in that it may be used to infer the causes of the spatial distributions evident in the remotely sensed imagery. This is because modelling extends the analysis into the temporal and vertical domains. However, the value of combining CFD with remote sensing is limited by the quality and quantity of data available through surface observation and remote sensing, and the implications of this to the integration of CFD with remote sensing are discussed.

KW - Computational fluid dynamics

KW - Phytoplankton

KW - Chlorophyll index

KW - Loch Leven

U2 - 10.1016/S0034-4257(01)00244-9

DO - 10.1016/S0034-4257(01)00244-9

M3 - Journal article

VL - 79

SP - 116

EP - 122

JO - Remote Sensing of Environment

JF - Remote Sensing of Environment

SN - 0034-4257

IS - 1

ER -