EGU General Assembly 2008
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  List of Accepted Contributions - GM5.6 Remote Sensing of Rivers: Methods, Applications, and Theory (co-listed in HS)

Please, click Abstract Number to find the corresponding abstract as PDF file; if necessary, download Adobe Acrobat Reader 4.0 first to open the file. Any abstract may be freely reproduced for non-commercial, scientific purposes; however, the moral right of the author(s) to be identified as the author(s) of such abstracts is asserted.

Legleiter, C.; Roberts, D.
A forward image model for evaluating the utility of passive optical remotely sensed data in river research

Kooistra, L.; Sanchez, L.; Wamelink, W.; Schaepman, M.; Clevers, J.
Assessing and predicting vegetation structure in floodplain ecosystems: assimilation of imaging spectrometer derived variables into dynamic vegetation models

Marcus, A.; Fonstad, M.
Making remote sensing of rivers accessible for rivers scientists and managers: The remote sensing of rivers on-line tutorial project.

Schumann, G.; Pappenberger, F.; Matgen, P.
Estimating uncertainty associated with water stages from a single SAR image using a stepped GLUE approach

Bjerklie, D; Gardiner, N
Remotely sensed estimates of geomorphic and hydraulic characteristics to help elucidate fish evolution in the lower Congo River (withdrawn)

Brasington, J; Vericat, D; Wheaton, J; Hodge, R
Reach-scale retrieval of alluvial bed roughness

Bird, S.; Schwab, J.; Hogan, D.
River remote sensing beneath the riparian canopy

Gilvear, DJ
Identifying river habitats on small to medium size temperate streams using multi-spectral imagery; opportunities and limitations

Mason, D.; Bates, P.; Dall'Amico, J.
Calibration of uncertain river flood inundation models using remotely sensed water levels

Salama, S; Radwan, M
Integrated Applications of Remote Sensing and Hydrodynamic Modeling for Improved Water Quality Monitoring and Prediction of the Nile River (Rosetta Branch)

Notebaert, B.; Verstraeten, G.; Poesen, J.; Govers, G.
Identification of fluvial landscape elements from regionally available airborne LIDAR imagery

Notebaert, B.; Verstraeten, G.; Poesen, J.; Govers, G.
Quantitative applications of regional scale LIDAR imagery in fluvial geomorphology

Entwistle, NS; Heritage, GL; Johnson, K
Cluster detection and development using terrestrial laser scanning

Feurer, D.; Bailly, J.-S.; Puech, C.
Measuring depth of a clear, shallow, gravel-bed river by through-water photogrammetry with small format cameras and ultra light aircrafts

Kinzel , P.; Wright , C.; Nelson, J.
Mapping a shallow, braided river with the Experimental Advanced Airborne Research LiDAR (EAARL)

Millar, D
Using airborne LIDAR bathymetry to map shallow river environments: a successful pilot on the Colorado River

Cavalli, M. ; Mathys, N.; Jacome, A.
Quality and vertical accuracy assessment of airborne LiDAR data: a case study on the Draix basins (French Alps)

Bailly, J.S.; Le Coarer , Y. ; Allouis, T. ; Stigermark, C.J.; Languille, P.; Adermus, J.
Bathymetry with LiDAR on gravel bed-rivers: Quality and limits

Hilldale, R.C.
Using bathymetric LiDAR and 2-D hydraulic modeling to map riverine aquatic habitat

Puech, C. ; Bailly, J.S.; Le Coarer, Y. ; Feurer, D.
Morphologic segmentation of rivers from satellite high spatial resolution multi-spectral images

Thomas, M.; Delacourt, C.; Davy, P.; Moulin, L.; Lague, D.
Optimal detection and quantification of channel variability along braided river: the Hurunui's case (New Zealand).

Pain, C F ; Paron, P; Smith, M
Applied geomorphological mapping (AppGeMa): a working group of the International Association of Geomorphologists

Clarke, J D A; Pain, C F; Gibson, D; Wong, V; Apps, H
Remote sensing of fluvial architecture of the Murray River, southern Australia

Rubin, D.M.; Chezar, H.; Barnard, P.L.; Warrick, J.A.; Draut, A.E.
Instant Grainification: Real-Time Grain-Size Analysis from Digital Images in the Field

Carbonneau, P.E.; Dugdale, S.; Campbell, D.
Fluvial remote sensing applied to catchment scale water resource management

Surian, N.; Ziliani, L.
Using aerial photographs to analyse channel changes in large gravel-bed rivers: potential and limitations

Fonstad, M
Hyperscale, three-dimensional structure of the streams of the Edwards Plateau, Texas, by HAB-transformed digital orthophotoquad imagery

Vianello, A.; Cavalli, M.; Tarolli, P.; D'Agostino, V.
LiDAR and field surveys for channel morphology analysis

Tormos, T.; Durrieu, S.; Pascal, K.; Wasson, J.G.
An operational methodology for characterizing land use along river corridor from remote sensing imagery at large scale

Damis, J.; Delenne, C.; Bailly, J.S.; Puech, C.
Performances comparison of bathymetry on rivers from various visible high resolution images.

Lane, S.N.; Thomas, R.E.; Widdison, P.E.
Quantification of river channel change using archival digital image analysis

Allouis, T.; Bailly, J.S.
On the use of Raman, infra-red, and green waveforms in bathymetric LiDAR for very shallow waters.

Luck, M.; Maumenee, N.; Stanford, J.; Kimball, J.; Whited, D.; Chilcote, S.
Physical complexity of salmon-producing rivers of western North America using Landsat and ancillary data

Marcus, W.A.; Fonstad, M.A.
Creating the International Network of River Observatory Scientists (INROS)

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