Introduction: The Growing Use of Imagery in Fundamental and Applied River Sciences - Fluvial Remote Sensing for Science and Management - page 17

of changing climates and potentially warming rivers.
Chapter 6 deals with FRS methods applied to another
emerging impact of changing hydrologic cycles: flooding.
Chapter 7 deals with LiDAR technology and it's specific
application to river environments. This first section is
followed by a section of five chapters with a more
applied perspective and which focuses on 'Hyperspa-
tial to catchment-scale imagery'. Chapter 8 defines and
discusses the concept of 'Hyperspatial' imagery. Chapter 9
presents an extensive habitat mapping based on hyper-
spatial imagery. Chapter 10 examines howhigh resolution
imagery can be used to go beyond classic characterisation
and predict the evolution of riparian vegetation. Simi-
larly, Chapter 11 presents image-based characterisation
approaches which extend beyond local study areas and
can be applied to long reaches or even entire networks.
Finally, Chapter 12 examines the uses of remote sensing in
predicting the land-use changes of entire catchments (i.e.
watersheds). In the third and final section of the topic, we
examine the increasing use of ground-based (terrestrial)
remote sensing methods in river sciences. Chapter 13
considers the uses of image-based data acquisition in
indoor flume experiments. Chapter 14 examines the
application of ground-based LiDAR, usually called 'Ter-
restrial Laser Scanners' (TLS) to river sciences. Chapter 15
focuses on oblique and vertical ground-photos which can
provide millimetric spatial resolution for grain size or
grain morphometry at a very high temporal resolution.
These approaches provide powerful tools for small-scale
process monitoring. The final three chapters still use
imagery as their primary data source but they represent
a definite departure from areas which are normally con-
sidered as within the remit of remote sensing. Chapter 16
discusses the uses of videography in river monitoring
works. Chapter 17 discusses the uses of imagery in
the study of small individual lotic organisms. Finally,
Chapter 18 examines the use of photo-questionnaires in
the assessment of the societal value of rivers and asso-
ciated restoration works. Practical conclusions close the
volume in Chapter 19. This volume therefore introduces
the scope of research already achieved and shows that
the techniques now available can be the basis for further
exciting developments in the next few years ensuring the
field of Fluvial Remote Sensing is poised to achieve more
significant contributions. Locations of case-studies for
the different chapters are also available on line so as to
provide opportunities for readers to see in more detail
size, geometry and characters of the rivers and field sites
discussed in the volume (Figure 1.9).

References

An, S.Q., Zhao, D.H., Cai, Y., Jiang, H., Xu, D.L., and Zhang,
W.G. 2011. Estimation of water clarity in Taihu Lake and
surrounding rivers using Landsat imagery. Advances in Water
Resources , 34 (2), 165-173.
Aranuvachapun, S., and Walling, D.E. 1988. Landsat-mss radi-
ance as a measure of suspended sediment in the lower Yellow
River (Hwang Ho). Remote Sensing of Environment , 25 (2),
145-165. 10.1016/0034-4257(88)90098-3.
Bertoldi, W., Gurnell, A.M., and Drake, N.A. 2011. The topo-
graphic signature of vegetation development along a braided
river: Results of a combined analysis of airborne lidar, color
air photographs, and ground measurements. Water Resources
Research , 47 . 10.1029/2010WR010319.
Brodie, J., Schroeder, T., Rohde, K., Faithful, J., Masters, B.,
Dekker, A., Brando, V., and Maughan, M. 2010. Dispersal
of suspended sediments and nutrients in the Great Bar-
rier Reef lagoon during river-discharge events: conclusions
from satellite remote sensing and concurrent flood-plume
sampling. Marine and Freshwater Research , 61 (6), 651-664.
Buscombe, D., and Masselink, G. 2009. Grain-size information
from the statistical properties of digital images of sediment.
Sedimentology , 56 (2), 421-438.
Carbonneau, P.E. 2005. The threshold effect of image resolution
on image-based automated grain size mapping in fluvial
environments. Earth Surface Processes and Landforms , 30 (13),
1687-1693.
Carbonneau, P.E., Lane, S.N., and Bergeron, N.E. 2004.
Catchment-scale mapping of surface grain size in gravel
bed rivers using airborne digital imagery. Water Resources
Research , 40 (7). 10.1029/2003WR002759.
Chuvieco, E., and Alfredo, H. 2010. Fundamentals of Satellite
Remote Sensing , CRC Press, Taylor and Francis, Boca Raton.
448 pp.
Dunford, R., Hervoue, A., Piegay, H., Belletti, B., and Tremelo,
M.L. 2011. Analysis of post-flood recruitment patterns in
braided-channel rivers at multiple scales based on an image
series collected by unmanned uerial vehicles, ultra-light aerial
vehicles, and satellites. Giscience & Remote Sensing , 48 (1),
50-73.
Fausch, K.D., Torgersen, C.E., Baxter, C.V., and Li, H.W. 2002.
Landscapes to riverscapes: Bridging the gap between research
and conservation of stream fishes. Bioscience , 52 (6), 483-498.
Fonstad, M.A., and Marcus, W.A. 2010. High resolution, basin
extent observations and implications for understanding river
form and process. Earth Surface Processes and Landforms ,
35 (6), 680-698.
Forzieri, G.,Moser, G., Vivoni, E.R., Castelli, F., andCanovaro, F.
2010. Riparian vegetation mapping for hydraulic rough-
ness estimation using very high resolution remote sensing
data fusion. Journal of Hydraulic Engineering-Asce , 136 (11),
855-867.