Management Applications of Optical Remote Sensing in the Active River Channel - Fluvial Remote Sensing for Science and Management - page 24

Figure 2.2 Depth map for the McKenzie River above Springfield, Oregon, developed using the true color air photo to the left and the
HAB-2 technique (Fonstad and Marcus, 2005). Darker tones indicate deeper water, except where shadows obscure the water. Depths
in this reach vary from zero to approximately 1.2 m. Pixel resolution is

∼ 10 cm.

of spatial and spectral resolutions and environmental
conditions. One finding of particular note is that the best
depth estimates usually occurred when one of the ratio
bands was centered around 710 nm, due to the strong
absorption of near-infrared wavelengths by water, which
makes the remotely sensed signal highly responsive to
subtle variations in depth.
Finally, in addition to correlation approaches and phys-
ical models, classical photogramettry with stereo pairs can
provide high resolution, accurate results. Application of
these techniques to determine water depth is compli-
cated, however, by the need to know the height of the
water surface above the bed surface that is being mapped.
Westaway et al. (2000, 2001) solved this by identifying
water surface elevations at the channel edge and extend-
ing these water surfaces to the remainder of the channel.
More recently, Lane et al. (2010) coupled photogram-
metric depth estimation techniques with optical physics
to achieve accurate depth measurements in areas cov-
ered by only one photo (Table 2.1). To accomplish this,
they developed depth-reflectance relations in areas of
stereo coverage and then applied these relationships to
reflectance values in areas covered by only one photo.
Water clarity is the key limitation to all techniques
for measuring water depth with optical imagery.
The maximum depth that can be remotely measured
is the maximum water depth to which the light can
penetrate and return to the surface and be detected
by the sensor, which varies with water column optical

properties, wavelength, instrument sensitivity, and

substrate composition (Legleiter et al., 2004).

2.5 Channel change

Managers and researchers have long used aerial photo-
graphs to map channel boundaries, bars, floodplain cover,
erosion and other features (Gilvear and Bryant, 2003).
Channel change maps are important for documenting
flood hazard, erosion hazard, and changes in habitat
diversity, as well as for understanding the causes of those
changes. The concept behind using remote imagery to
create two dimensional planimetric channel change maps
is simple: features visible on air photos can be traced
or digitised and transferred to map coordinates, and if
images are available from different dates, the maps can be
overlain to document change over time.
A major component of channel change often relates
to the introduction of human features such as groynes
and weirs. These features often stand out clearly on ver-
tical images because of their shape and texture, which
make them jump out to the naked eye, and because of
their different composition relative to surrounding mate-
rials, which enables their detection through automated,
spectrally-based techniques. However, when covered by
vegetation or buried in sediments, remote sensing may
well miss features of this nature.