Hydrolight simulations. An efficient, direct solution of the inversion model was
obtained using a matrix inversion method (MIM). The MIM was performed on each
pixel of a Hyperion scene for Deception Bay. Maps of chl a, tripton, and CDOM were
produced which had impressive accuracy and precision. Sensitivity analyses
demonstrated that Hyperion could resolve constituents at the following intervals: chl a
= 2.32 µg/l, tripton = 12.5 mg/l, and CDOM = 0.21 m
-1
. The authors concluded that the
procedure will require a much more thorough measurement of the spatial and temporal
variation in SIOPs before accuracy can be further improved and the technique can be
applied more broadly to optically diverse coastal waters.
12. Summary and Recommendations
Remote sensing procedures for chl a are becoming operational in coastal waters.
However, these waters may quite possibly represent the most diverse optical conditions,
in space and time, of any aquatic habitat. The ability to detect chl a in coastal waters is
complicated by: 1) the large dynamic range of pigment in coastal waters; 2) a
dominance of water optics by CDOM and/or tripton in many situations; 3) the spatial
and temporal dynamics of coastal hydrology; 4) the diverse nature of the optical
constituents and their SIOPs; 5) atmospheric aerosols and the requirement for accurate
atmospheric corrections; 6) water density gradients and light and nutrient induced, nonuniform vertical distributions; 7) bottom reflectance and the diversity of benthic
substrates; and 8) the problem of mixed pixels related to spatial resolution and
contributions from shore zones. These challenges have required a redirection of optics
research and remote sensing operational schemes for the Case 2 water conditions
prevalent in most coastal settings.
The ability to detect chlorophyll in Case 2 waters requires, especially,
hyperspectral data with the resolution to detect sometimes subtle pigment absorption
bands, different accessory pigments, shoulders and peaks in reflectance spectra related
to scattering and fluorescence activities, and good calibration and accuracy of
instruments. The red and lower NIR spectral regions are often the most favorable for
chl a detection in Case 2 waters because: 1) accessory pigments have minimal
contribution to total absorption at these wavelengths; 2) CDOM and organic tripton
have reduced absorption; and 3) the NIR peak feature in reflectance is more sensitive to
the higher chl a ranges found in coastal waters. On the other hand, this wavelength
range is less practical for lower chl a ranges because of dominance by water absorption.
Ocean color algorithms utilizing blue and green spectral bands are appropriate
when Case 1 conditions occur in coastal waters. Pixel classification procedures may be
required to make an initial examination of reflectance pattern and the selection of the
most appropriate algorithm and parameterizations. However, the techniques for Case 2
water measurements reviewed in this chapter may also hold promise for the open
oceans and other Case 1 waters such as large lakes (International Ocean-Color
Coordinating Group, 2000). The challenges of Case 2 water optics have stimulated
significant advancements in bio-optical modeling and insights into the interactions of
optical constituents. Case 1 algorithms rely on an assumed covariance of constituents,
whereas the techniques for relating Case 2 constituents to reflectance signals often
require multivariate, non-linear models (International Ocean-Color Coordinating
Group, 2000).
The best procedures to apply in a given situation often are decided by constraints
of time, money, and resolution requirements of the user. In some cases, detection of
73
Optical Remote Sensing Techniques
obtained using a matrix inversion method (MIM). The MIM was performed on each
pixel of a Hyperion scene for Deception Bay. Maps of chl a, tripton, and CDOM were
produced which had impressive accuracy and precision. Sensitivity analyses
demonstrated that Hyperion could resolve constituents at the following intervals: chl a
= 2.32 µg/l, tripton = 12.5 mg/l, and CDOM = 0.21 m
-1
. The authors concluded that the
procedure will require a much more thorough measurement of the spatial and temporal
variation in SIOPs before accuracy can be further improved and the technique can be
applied more broadly to optically diverse coastal waters.
12. Summary and Recommendations
Remote sensing procedures for chl a are becoming operational in coastal waters.
However, these waters may quite possibly represent the most diverse optical conditions,
in space and time, of any aquatic habitat. The ability to detect chl a in coastal waters is
complicated by: 1) the large dynamic range of pigment in coastal waters; 2) a
dominance of water optics by CDOM and/or tripton in many situations; 3) the spatial
and temporal dynamics of coastal hydrology; 4) the diverse nature of the optical
constituents and their SIOPs; 5) atmospheric aerosols and the requirement for accurate
atmospheric corrections; 6) water density gradients and light and nutrient induced, nonuniform vertical distributions; 7) bottom reflectance and the diversity of benthic
substrates; and 8) the problem of mixed pixels related to spatial resolution and
contributions from shore zones. These challenges have required a redirection of optics
research and remote sensing operational schemes for the Case 2 water conditions
prevalent in most coastal settings.
The ability to detect chlorophyll in Case 2 waters requires, especially,
hyperspectral data with the resolution to detect sometimes subtle pigment absorption
bands, different accessory pigments, shoulders and peaks in reflectance spectra related
to scattering and fluorescence activities, and good calibration and accuracy of
instruments. The red and lower NIR spectral regions are often the most favorable for
chl a detection in Case 2 waters because: 1) accessory pigments have minimal
contribution to total absorption at these wavelengths; 2) CDOM and organic tripton
have reduced absorption; and 3) the NIR peak feature in reflectance is more sensitive to
the higher chl a ranges found in coastal waters. On the other hand, this wavelength
range is less practical for lower chl a ranges because of dominance by water absorption.
Ocean color algorithms utilizing blue and green spectral bands are appropriate
when Case 1 conditions occur in coastal waters. Pixel classification procedures may be
required to make an initial examination of reflectance pattern and the selection of the
most appropriate algorithm and parameterizations. However, the techniques for Case 2
water measurements reviewed in this chapter may also hold promise for the open
oceans and other Case 1 waters such as large lakes (International Ocean-Color
Coordinating Group, 2000). The challenges of Case 2 water optics have stimulated
significant advancements in bio-optical modeling and insights into the interactions of
optical constituents. Case 1 algorithms rely on an assumed covariance of constituents,
whereas the techniques for relating Case 2 constituents to reflectance signals often
require multivariate, non-linear models (International Ocean-Color Coordinating
Group, 2000).
The best procedures to apply in a given situation often are decided by constraints
of time, money, and resolution requirements of the user. In some cases, detection of
73
Optical Remote Sensing Techniques