Applications of Close-range Imagery in River Research - Fluvial Remote Sensing for Science and Management - page 348

river ice widths can be hazardous and time consuming to
realise, especially in remote locations at temperatures far
below zero Celsius. In this example, the 24 pictures were
taken everyday in less than 30 minutes, minimising time
in the field and maximising data analysis time back in a
warmer laboratory.

methods. This method reduces the amount of field work
necessary to survey a large area along a river corridor
and allows a rapid assessment of the spatial variability of
riparian vegetation.
A second example of using close-range imagery to
understand riparian forest processes exploits the advan-
tages of oblique photographs and the rapid coverage of
long river reaches from a helicopter platform. For man-
agement purposes, accurate geomorphic description is
often required for long lengths of river channel in order
to target specific actions. Traditional aerial photographic
surveys and/or lidar surveys cannot provide high quality
information about surface topography with a high rate
of elevation change, such as natural river banks, riprap
emplacements or dikes. Moreover, some detailed features
such as boulders, rock outcrops or wood pieces are not
easily detected from aerial photos for which the resolu-
tion is 20 to 50 cm. In such a context, oblique close-range
photos taken from helicopter can be a valuable source of
data. Such monitoring campaigns were conducted along
the Ain River (40 km long, in 1989 and in 1999), the
Drome River (95 km long, in 1995), and the Eygues River
(100 km long, in 2000). Photographs of one bank mov-
ing from upstream to downstream and of the other one
when returning were acquired continuously providing
400 to ca 1500 photographs during a single flight (4-15
photos per km). Visual observation of these images plus
linear measurements, as well as object identification and
counting can then provide information about longitudi-
nal patterns of geomorphic features (Piegay and Landon,
1997; Landon et al., 1998; Piegay et al., 2000; Lassettre
et al., 2007).
On the Dr ome, the campaign was taken at a mean
daily discharge of 18.4 m 3 s − 1 (120 days/year), providing
information on bars and banks. The survey quantified the
distribution of boulders (

15.4.6 Riparianstructureanddeadwood
distributionsalongriver corridors
Close range imagery allows the analysis of riparian canopy
structure and in particular gives the possibility to assess
vegetation density and therefore channel shading, which
is an important aspect of in-channel habitat. The canopy
affects water temperature by intercepting and emitting
radiation and also influences local humidity, air flow and
air temperature (Kelley and Krueger, 2005). In alluvial for-
est, light controls species composition and regeneration
and interacts with flow and morphological disturbances
to control vegetation dynamics (Hall and Harcombe,
1998). There is then a clear need to evaluate light trans-
fer under the forest canopy to understand undergrowth
vegetation patterns and distinguish the respective contri-
butions of available light and erosion or sedimentation
disturbances in controlling species distributions. This
question is also meaningful when working on aquatic
communities and evaluating the effect of canopy shad-
ing on invertebrate communities (Behmer and Hawkins,
2006). Davies-Colley and Payne (1998) highlighted the
lack of quantitative assessments of channel shading and
reviewed a variety of alternative approaches.
A variety of methods have been developed for measur-
ing canopy cover, and thus inferring the level of shading
in the channel. Kelley and Krueger (2005) assessed two
traditional methods for measuring canopy cover (a cli-
nometer, used to measure the angle between the horizon
and the edge of the canopy, and a densitometer, a con-
vex mirror used to estimate the proportion of the sky
that is obscured) against a digital imaging method. The
digital imaging method utilised a camera fitted with a
180 ◦ fish-eye lens pointed vertically to capture a complete
hemispheric image of the canopy from below. Specialist
image analysis software (HemiView; delta-t.co.uk) seg-
ments the image to separate areas of canopy from sky
and, with the addition of camera orientation, location,
elevation and date, models the proportion of total avail-
able solar radiation that reaches the water surface during
the course of a year. Kelley and Krueger (2005) concluded
that hemispherical image analysis was both more consis-
tent and required smaller sample sizes than the alternative

256 mm), pools, in-channel
and in-bar wood pieces (greater than 20 cm in diameter
and 10 m in length), in-channel bedrock surfaces and also
provided continuous information on bank characteris-
tics (e.g. floodplain or valley wall, eroded or embanked).
This data set, divided in homogeneous segments 500 m
long, was used to compute a Habitat Richness Index per
section (see details in Piegay et al. 2000). Figure 15.13
(a and b) shows examples of oblique photos on which
bank states were observed and mapped. This information
was tabulated for 500 m length sections to provide overall
statistics and a synoptic view of longitudinal changes.
Eroded bank cumulated lengths (right versus left banks)
were calculated from km 0 (the Rh one confluence) to
km 95 upstream. Figure 15.13c indicates that the reach

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