82
Remote Sensing Techniques
The advent of ocean color satellites provides an opportunity to measure aquatic biology from space
with global coverage and near-daily temporal resolution. The Coastal Zone Color Scanner provided
limited data through the late 1970s and early 1980s
and the Sea WiFS satellite now provides global resolution on a daily basis (e.g., Gordon and Morel
1983; McClain et al. 1998). This has resulted in a
suite of bio-optical approaches for determining primary production from space-based platforms (e.g.,
Platt et al. 1991; Bidigare et al. 1992; Antoine and
Morel, 1996; Behrenfeld and Falkowski, 1997).
Ocean color satellites work by measuring the
amount of upwelled radiance from the earth's surface in a limited number of visible wavelengths.
They provide a spatial resolution of about 1 km and
thus can be usable for larger lakes and the oceans.
However, the data from these satellites can be quite
tricky to work with. First, there are nontrivial issues
associated with determining the stability and accuracy of the satellite-determined radiance measurements and correcting them for atmospheric influences. This provides a determination of the water
leaving radiance, or the ocean color spectrum.
The second complicating factor is the conversion
of the ocean color spectrum into a measurement of
interest, such as the chlorophyll concentration. An
excellent comparison of methods to determine
chlorophyll from ocean color determinations can be
found in O'Reilly et al. (1998). Other recent techniques allow for the determination of the amount
of chlorophyll, detritus, and colored organic material concentrations, as well as particulate backscattering intensity (e.g., Garver and Siegel, 1997).
The third major issue is the specification of
photo-physiological parameters (P vs. I characteristics, quantum yields for carbon assimilation, etc.)
for use in bio-optical primary production models.
A variety of approaches have been used. Some investigators assume that these parameters are fixed
for a given biogeochemical province (e.g., Platt et
al. 1991). Obviously, this method subsumes much
of the natural ecosystem variability into the algorithm. Other investigators parameterize them in
terms of measurable quantities (e.g., Bidigare et al.
1992; Antoine and Morel, 1996). In all, the success
of these approaches is rather poor, accounting for
Robert W. Howarth and Anthony F. Michaels
30 to 40% of the variability in production within
an ecosystem and not much more when evaluated
globally (e.g., Balch et al. 1992; Campbell and
O'Reilly, 1988; Siegel et al. 1995). However, all of
these remote sensing techniques make up for their
accuracy limitations by the enormous increase in
information on spatial and temporal patterns that
are seen from space. Carefully used in conjunction
with field measurements, these tools can and will
help to revolutionize our understanding of aquatic
productivity.
Acknowledgments Dave Siegel provided valuable
advice on remote sensing techniques. We thank
Tom Butler, Jon Cole, and Roxanne Marino for
helpful comments on an earlier draft of this chapter.
Preparation of the manuscript was supported in part
by a grant to RWH from the Hudson River Foundation, a not-for-profit foundation with headquarters in New York.
References
Antoine, D.; and Morel, A. Oceanic primary production.
1. Adaptation of a spectral light-photosynthesis model
in view of application to satellite chlorophyll observations. Global Biogeochem. eycl. 10:43-55; 1996.
Arlstegui, J.; Monero, M.E; Ballesteros, S.; Basterretxea,
G.; van Lenning, K Planktonic primary production
and microbial respiration measured by 14C assimilation and dissolved oxygen changes in coastal waters
of the Antarctic peninsula during austral summer: Implications for carbon flux studies. Mar. Ecol. Prog. Ser.
132:191-201; 1996.
Balch, W.M., Evans, R.; Brown, J.; Feldman, G.; McClain, c.; W. Esaias, W. The remote sensing of ocean
primary productivity-the use of a new data compilation to test satellite algorithms. J. Geophys. Res.
97:2279-2293; 1992.
Behrenfeld, MJ.; and Falkowski, P.G. Photosynthetic
rates derived from satellite-based chlorophyll concentration. Limnol. Oceanogr. 42:1-20; 1997.
Bender, M.; Grande, K; Johnson, K; Marra, J.; Williams, P.J.L.; Sieburth, J.; Milson, M.; Langdon, C.;
Hitchock, G.; Orchardo, J.; Hunt, C.; Donaghay, P.;
Heinemann, K A comparison of four methods for determining planktonic community production. Limnol.
Oceanogr. 32:1085-1098; 1987.
Bennet, J.P.; Rathbun, R.E. Reaeration in Open-Channel
Flow. U.S. Geological Survey (USGS) Paper 737.
Remote Sensing Techniques
The advent of ocean color satellites provides an opportunity to measure aquatic biology from space
with global coverage and near-daily temporal resolution. The Coastal Zone Color Scanner provided
limited data through the late 1970s and early 1980s
and the Sea WiFS satellite now provides global resolution on a daily basis (e.g., Gordon and Morel
1983; McClain et al. 1998). This has resulted in a
suite of bio-optical approaches for determining primary production from space-based platforms (e.g.,
Platt et al. 1991; Bidigare et al. 1992; Antoine and
Morel, 1996; Behrenfeld and Falkowski, 1997).
Ocean color satellites work by measuring the
amount of upwelled radiance from the earth's surface in a limited number of visible wavelengths.
They provide a spatial resolution of about 1 km and
thus can be usable for larger lakes and the oceans.
However, the data from these satellites can be quite
tricky to work with. First, there are nontrivial issues
associated with determining the stability and accuracy of the satellite-determined radiance measurements and correcting them for atmospheric influences. This provides a determination of the water
leaving radiance, or the ocean color spectrum.
The second complicating factor is the conversion
of the ocean color spectrum into a measurement of
interest, such as the chlorophyll concentration. An
excellent comparison of methods to determine
chlorophyll from ocean color determinations can be
found in O'Reilly et al. (1998). Other recent techniques allow for the determination of the amount
of chlorophyll, detritus, and colored organic material concentrations, as well as particulate backscattering intensity (e.g., Garver and Siegel, 1997).
The third major issue is the specification of
photo-physiological parameters (P vs. I characteristics, quantum yields for carbon assimilation, etc.)
for use in bio-optical primary production models.
A variety of approaches have been used. Some investigators assume that these parameters are fixed
for a given biogeochemical province (e.g., Platt et
al. 1991). Obviously, this method subsumes much
of the natural ecosystem variability into the algorithm. Other investigators parameterize them in
terms of measurable quantities (e.g., Bidigare et al.
1992; Antoine and Morel, 1996). In all, the success
of these approaches is rather poor, accounting for
Robert W. Howarth and Anthony F. Michaels
30 to 40% of the variability in production within
an ecosystem and not much more when evaluated
globally (e.g., Balch et al. 1992; Campbell and
O'Reilly, 1988; Siegel et al. 1995). However, all of
these remote sensing techniques make up for their
accuracy limitations by the enormous increase in
information on spatial and temporal patterns that
are seen from space. Carefully used in conjunction
with field measurements, these tools can and will
help to revolutionize our understanding of aquatic
productivity.
Acknowledgments Dave Siegel provided valuable
advice on remote sensing techniques. We thank
Tom Butler, Jon Cole, and Roxanne Marino for
helpful comments on an earlier draft of this chapter.
Preparation of the manuscript was supported in part
by a grant to RWH from the Hudson River Foundation, a not-for-profit foundation with headquarters in New York.
References
Antoine, D.; and Morel, A. Oceanic primary production.
1. Adaptation of a spectral light-photosynthesis model
in view of application to satellite chlorophyll observations. Global Biogeochem. eycl. 10:43-55; 1996.
Arlstegui, J.; Monero, M.E; Ballesteros, S.; Basterretxea,
G.; van Lenning, K Planktonic primary production
and microbial respiration measured by 14C assimilation and dissolved oxygen changes in coastal waters
of the Antarctic peninsula during austral summer: Implications for carbon flux studies. Mar. Ecol. Prog. Ser.
132:191-201; 1996.
Balch, W.M., Evans, R.; Brown, J.; Feldman, G.; McClain, c.; W. Esaias, W. The remote sensing of ocean
primary productivity-the use of a new data compilation to test satellite algorithms. J. Geophys. Res.
97:2279-2293; 1992.
Behrenfeld, MJ.; and Falkowski, P.G. Photosynthetic
rates derived from satellite-based chlorophyll concentration. Limnol. Oceanogr. 42:1-20; 1997.
Bender, M.; Grande, K; Johnson, K; Marra, J.; Williams, P.J.L.; Sieburth, J.; Milson, M.; Langdon, C.;
Hitchock, G.; Orchardo, J.; Hunt, C.; Donaghay, P.;
Heinemann, K A comparison of four methods for determining planktonic community production. Limnol.
Oceanogr. 32:1085-1098; 1987.
Bennet, J.P.; Rathbun, R.E. Reaeration in Open-Channel
Flow. U.S. Geological Survey (USGS) Paper 737.