Dr Patrice Carbonneau patrice.carbonneau@durham.ac.uk
Associate Professor
Recent research has demonstrated that image processing can be applied to derive surficial median grain size data automatically from high-resolution airborne digital imagery in fluvial environments. However, at the present time, automated grain size measurement is limited to the dry exposed bed areas of the channel. This paper shows that the application area of automated grain size mapping can be extended in order to include the shallow wetted areas of the channel. The paper then proceeds to illustrate how automated grain size measurement in both dry and shallow wetted areas can be used to measure grain sizes automatically for long river lengths. For the present study, this results in a median grain size profile covering an 80 km long river which is constructed from over three million automated grain size measurements.
Carbonneau, P., Bergeron, N., & Lane, S. (2005). Automated grain size measurements from airborne remote sensing for long profile measurements of fluvial grain sizes. Water Resources Research, 41(11), Article W11426. https://doi.org/10.1029/2005wr003994
Journal Article Type | Article |
---|---|
Publication Date | Nov 24, 2005 |
Deposit Date | Oct 6, 2008 |
Publicly Available Date | Mar 24, 2010 |
Journal | Water Resources Research |
Print ISSN | 0043-1397 |
Electronic ISSN | 1944-7973 |
Publisher | Wiley |
Peer Reviewed | Peer Reviewed |
Volume | 41 |
Issue | 11 |
Article Number | W11426 |
DOI | https://doi.org/10.1029/2005wr003994 |
Keywords | Remote sensing, Gravel bed rivers, Automated grain size measurement. |
Public URL | https://durham-repository.worktribe.com/output/1567369 |
Published Journal Article
(612 Kb)
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Copyright Statement
© 2005 American Geophysical Union. Carbonneau, P. E., Bergeron, N. E., Lane, S. N., (2005) 'Automated grain size measurements from airborne remote sensing for long profile measurements of fluvial grain sizes.', Water resources research, 41, W11426, 10.1029/2005WR003994 (DOI). To view the published open abstract, go to http://dx.doi.org and enter the DOI.
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