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- H31K-1205: Capturing the short-term evolution of complex river channel morphology with repeat lidar point clouds
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Board 1205‚ Hall EFG (Poster Hall)NOLA CC
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Mariel Nelson, University of Texas at Austin (First Author, Presenting Author)
Timothy Goudge, University of Texas at Austin
David Mohrig, University of Texas at Austin
This project addresses fundamental challenges in measuring the shape and evolution of river channels by advancing lidar remote sensing analysis methods. Though rivers control water, sediment, and nutrient transport through landscapes, measuring how they change in response to floods is difficult. This is because river banks are hard to map—they are often steep, curved, and covered by vegetation. Typical mapping strategies cannot accurately capture the shape of steep channel banks over multiple river bends. To address this, we present a data processing pipeline that increases the usability of existing topographic datasets to improve understanding of river channel dynamics.We highlight two primary innovations that are applied to both airplane and drone lidar datasets. First, we show that relabeling data using new geometric criteria can recover ground surface measurements that were incorrectly labeled as non-ground features. This increases measurement density and spatial coverage on steep bank surfaces. Second, we analyze channel shape changes mapped with lidar dataset pairs. We do this by reconstructing 3D volumes around eroded regions. This approach uses the full channel shape information contained in the underlying datasets, increasing our ability to capture subtle changes on steep and rapidly-changing landforms.
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