Abstract

Change detection of high resolution topographic data is commonly used in river valleys to quantify reach- and site-scale sediment budgets by estimating the erosion/deposition volume, and to interpret the geomorphic processes driving erosion and deposition. Field survey data are typically collected as point clouds that are often converted to gridded raster datasets and the ultimate choice of grid resolution is left to the user. This choice may have important implications for both the quantification and interpretation of geomorphic change. Here we used concurrent topographic data collected by terrestrial laser scanning (TLS) and structure-from-motion (SfM) photogrammetry to quantify the influence of grid resolution and sampling technique on (a)the sediment budget and (b)the presence and role of geomorphic processes (i.e.,alluvial, colluvial, aeolian, and fluvial transport) driving topographic change at four sites along the Colorado River in Grand Canyon, Arizona, USA. We found that while both techniques produced similar estimates for site-scale sediment budgets, the magnitude of detected topographic change was dampened at coarser pixel resolutions. An overall decrease in the areal extent of erosion and deposition were observed, respectively, when coarsening pixel size from 5cm to 1m among all sites. Coarser resolution data tended to affect interpretation of landscape change along the margins of river valleys. For example, when changing from 5cm to 1m pixel resolution, the inferred contribution of aeolian changes to total site-scale geomorphic change increased in area by 7.9%, whereas the inferred contribution of alluvial and colluvial processes decreased in area by 97.9% and 88.2%, respectively. More generally, we found that coarsening pixel sizes disproportionately attributed geomorphic change to one or more of the most common processes operating at a site. We also found that coarsening pixel resolution amplified the net sediment imbalance at the site scale, driving the imbalance at erosional sites further into erosion and vice versa for depositional sites. Our results have implications both for point cloud data collection and for raster dataset processing. We argue that selecting the finest obtainable resolution is not always warranted to accurately quantify and interpret geomorphic change, because remote sensing technique, topographic data resolution, and analysis procedure can be optimized to capture the spatial scale of those processes driving landscape change. However, in landscapes at or near sediment equilibrium (i.e.,equal amounts of erosion and deposition), thefinest obtainable topographic data resolution is warranted to avoid amplifying sediment imbalance and erroneously inferring that sites are trending toward erosion or deposition.

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