Ground based LiDAR and its Application to the Characterisation of Fluvial Forms - Fluvial Remote Sensing for Science and Management - page 328

(c) tilt the scanner towards the river channel tomaximise
the amount of data collected locally;
(d) select scan locations to minimise scan shadow effects
caused by large obstructions;
(e) where possible, optimise the scan angle by setting the
instrument well above the scanned surface;
(f) collect independent tiepoint/error check data to
minimise systematic bias introduced during scan cloud
merging;
(g) use manually selected tiepoints for more accurate
scan merging due to the ability to select their location in
the scan data with high precision;
(h) ensure that some reflectors/tiepoints are placed at the
edges of the scanned area to minimise propagation of
meshing errors;
(i) ensure a good variation in x , y and z dimensions when
selecting tiepoints/reflector locations; this improves scan
merging accuracy and reduces the possibility of 'chance'
scan merging due to similar distances and elevations
between tiepoints or reflectors;
(j) repeat scans from the same location to densify the
data collected and potentially reduce extreme errors; and
(k) avoid low angle scans across water surfaces.
In conclusion, the ability to survey a river channel
rapidly enough to capture changes between floods at a
high spatial resolution is one of the biggest limitations
when surveying morphology in the field, and this prob-
lem is particularly applicable to more active (e.g. braided)
river systems. Using terrestrial laser scanning however,
the issue of point distribution and potential operator bias
(Lane et al., 2003) can be rendered obsolete as a dense
cloud of meshed data points ensures that a surface is
sampled many times. If proper collection and analyti-
cal protocols can be put in place, and data archiving
and mining issues standardised, we may even get close
to the situation described by Lane et al. 2003 where
the authors state that 'just as theoretical debates ... are
asking that we take a more holistic view of landform
processes, so data collection systems are getting dan-
gerously close to providing a resolution of data that
can satisfy the reductionist tendencies of some without
precluding this wider view'. Despite this assertion, data
point quality may still potentially prove to be an issue
for some studies aimed at the grain scale as the range
error on current instruments may still lead to unaccept-
able inaccuracies in the DEM surface. New advances in
ground-based LiDAR technology aim at addressing such
outstanding issues.

References

Boehler, W., Bordas-Vincent, M., and Marbs, A. 2003. Investi-
gating laser scanner accuracy, Proceedings of the 19th CIPA
Symposium, 30 th September - 4 th October 2003, Antalya,

Turkey.
Brasington, J., Rumsby, B.T., andMcVey, R.A. 2000. Monitoring
and modelling morphological change in a braided gravel-bed
river using high-resolution GPS-based survey. Earth Surface
Processes and Landforms 25 : 973-990.
Brayshaw, A.C. 1984. Characteristics and origin of cluster bed-
forms in coarse-grained alluvial channels. Sedimentology of
Gravels and Conglomerates 10 : 77-85.
Charlton, M.E., Large, A.R.G., and Fuller, I.C. 2003. Application
of airborne LiDAR in river environments: the River Coquet,
Northumberland, UK. Earth Surface Processes and Landforms
28 : 299-306.
Crutchley, S. 2009. Using LiDAR in archaeological contexts: the
English Heritage experience and lessons learned. 180-200 in
Heritage, G.L. and Large, A.R.G. (eds). Laser Scanning for the
Environmental Sciences. London: Wiley-Blackwell.
Cui, Y.T.,Wooster, J.K., Venditti, J.G., Dusterhoff, S.R., Dietrich,
W.E., and Sklar, L.S. 2008. Simulating sediment transport in
a flume with forced pool-riffle morphology: Examinations of
two one-dimensional numerical models. Journal of Hydraulic
Engineering-ASCE 134 : 892-904.
Danson, F.M., Morsdorf, F., and Koetz, B. 2009. Airborne and
terrestrial laser scanning for measuring vegetation canopy
structure. 201-219 in Heritage, G.L. and Large, A.R.G. (eds).
Laser Scanning for the Environmental Sciences . London: Wiley-
Blackwell.
EAMN (European Aquatic Monitoring Network). 2004. State-
of-the-art in data sampling, modelling analysis and applications
of river habitat modelling . (Harby, A., Baptist, M., Dunbar,
M.J., and Schmutz. S. (eds). COST Action 626 Report.
Entwistle, N.S. and Fuller, I.C. 2009. Terrestrial laser scanning
to derive the surface grain size facies character of gravel
bars. 102-114 in Heritage, G.L. and Large, A.R.G., (eds).
Laser Scanning for the Environmental Sciences . London: Wiley-
Blackwell.
Fuller, I.C., Large, A.R.G., and Milan, D.J. 2003. Quantifying
channel development and sediment transfer following chute
cutoff in a wandering ravel-bed river. Geomorphology 54 :
307-323.
Gomez, B. 1993. Roughness of stable, armoured gravel beds.
Water Resources Research , 29 : 3631-3642.
Heritage, G.L. and Large, A.R.G. (eds) (2009a). Laser Scanning for
the Environmental Sciences . London: Wiley-Blackwell. 278 p.
Heritage, G.L. and Large, A.R.G. (2009b). Principles of 3D
laser scanning. 21-34 in Heritage, G.L. and Large, A.R.G.
(eds). Laser Scanning for the Environmental Sciences . London:
Wiley-Blackwell.