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Smith, 2001). Turbidity in and of itself is an important
component of water quality that controls light avail-
ability for photosynthetic organisms. Turbidity is also
an important control on other remote sensing applica-
tions in rivers; for example, depth estimates from optical
imagery are far less likely to be reliable where the bottom is
obscured (Figure 2.3). Finally, because turbidity is related
to sediment concentrations, its measurement can provide
information on timing of sediment movement, variability
in sediment sources, and (when coupled with discharge
data) sediment load, although some approaches move
directly from pixel values to suspended sediment concen-
trations without reference to turbidity (e.g. Pavelsky and
Smith, 2009).
There is an extensive literature describing the use of
optical imagery to monitor turbidity and, to a lesser
degree, suspended sediment concentrations. When
suspended sediments are remotely mapped, it is usually
accomplished
measurements of suspended sediment concentrations
then generates an estimate of suspended sediment
concentrations. Because optical remote sensing images
the upper portion of the water column where suspended
sediment concentrations are usually lower, remote
sensing approaches may underestimate depth-integrated
suspended sediment concentrations.
The vast majority of literature on turbidity and
sediment concentrations focuses on oceans, lakes
and estuaries. The research that does exist for rivers
focuses almost entirely on large systems like the Amazon
(Mertes et al., 1993), Yellow (Aranuvachapun and
Walling, 1988) or Yangtze Rivers (Liu et al., 2008), where
turbidity, suspended sediment concentrations, and sur-
face characteristics of the streams are relatively constant
over long reaches. In contrast, a large host of factors
in smaller systems alter the relation between turbidity,
suspended sediment concentrations, and reflected light
over short distances. Surface turbulence, water depth,
substrate colour and size, aquatic vegetation, sun angle
relative to the water, and local variations in sediment
colour all can alter the signal received by the sensor
independent of any actual changes in turbidity. Different
inputs and variable timing of flow from tributaries also
can alter the correlations between turbidity and sediment
concentrations. In short, it remains difficult to accurately
map turbidity and suspended sediment concentrations
in small and medium streams with remote sensing.
The majority of approaches for estimating turbidity or
sediment concentrations use field measurements to estab-
lish empirical relations between image values, turbidity,
and suspended sediment. Mertes et al. (2002) provide an
overview of image processing techniques for mapping sus-
pended sediment concentrations. Presently, there are no
widely accepted standard approaches for setting up these
empirical relationships. Most researchers use some com-
bination of red and/or near infrared bands to map turbid-
ity, although green bands can be of use, especially when
chlorophyll concentrations strongly influence turbidity.
The relationships set up between sediment concentra-
tions or turbidity and spectral signatures include spectral
mixture analysis (Mertes, 1993), simple logarithmic rela-
tions (Aranuvachapun and Walling, 1988), normalised
difference relations (Han et al., 2006), simple regression
(Wang et al., 2009), multiple regression (Shibayama et al.,
2007), General Additive Models (Bustamante et al., 2009)
and neural networks (Teodoro et al., 2008). As of now,
researchers seem inclined to choose the method that
generates the best fit to the field data without having
strong theoretical arguments for choosing one method
via
remote
mapping
of
the
turbidity.
A
correlation
between
turbidity
and
ground-based
Figure 2.3
Aerial image of the confluence of Soda Butte Creek
(left) and the Lamar River (right), Wyoming, USA. The
turbidity in Soda Butte Creek prevents light penetration of the
water column, which in turn limits measurement of depths,
substrates size, or other features below the water surface. If
ground measurements are available to calibrate image
reflectance to turbidity, however, the imagery can be used to
map turbidity and suspended sediment concentrations in the
two streams.
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