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Qualitative and quantitative applications of LiDAR imagery in fluvial geomorphology
Authors:Bastiaan Notebaert  Gert Verstraeten  Gerard Govers  Jean Poesen
Institution:Physical and Regional Geography Research Group, K.U. Leuven, Celestijnenlaan 200E, box 2409, B‐3001 Leuven, Belgium
Abstract:The potential for geomorphological mapping and quantitative calculations of light detection and ranging (LiDAR) data within fluvial geomorphology was studied for two river catchments within Belgium (Dijle and Amblève), which differ in physical settings and floodplain morphology. Two commercial, of‐the‐shelf LiDAR datasets with different specifications (horizontal resolution and vertical accuracy) were available for parts of the floodplains of both catchments. Real‐time kinematic (RTK) Global Positioning System (GPS) data were used as ground truth for error calculations. Qualitative analysis of LiDAR data allowed the identification of former channel patterns, levees, colluvial hillslope and fan deposits. These results were confirmed by field data, topographic surveys and historical maps. The pixel resolution proved to be an important factor in the identification of small landforms: only features with a width equal to or larger than LiDAR resolution can be detected. This poses limits on the usability of regionally available LiDAR data, which often have a horizontal resolution of several metres. The LiDAR data were also used in a quantitative analysis of channel dynamics. In the study area, the width of the Dijle River channel increased 3 m on average between 1969 and 2003. A sediment budget of channel processes for the period 1969–2003 indicated a total river bank erosion of 16·1 103 m3 and a total within channel deposition of 7·1 103 m3, resulting in a net river erosion of 9·0 103 m3 or c. 0·4 Mg year?1 per metre river length. Sequential LiDAR data can in theory be used to calculate vertical sedimentation rates, as long as there is control on the error of the reference levels used. Copyright © 2008 John Wiley and Sons, Ltd.
Keywords:LiDAR  remote sensing  fluvial geomorphology  Belgium
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