The Experts below are selected from a list of 6930 Experts worldwide ranked by ideXlab platform
Joel B Sankey - One of the best experts on this subject based on the ideXlab platform.
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The effects of topographic surveying technique and data resolution on the detection and interpretation of Geomorphic Change
Geomorphology, 2019Co-Authors: Alan Kasprak, Joel B Sankey, Joshua Caster, Nathaniel D. Bransky, Temuulen T. SankeyAbstract: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 5 cm to 1 m among all sites. Coarser resolution data tended to affect interpretation of landscape Change along the margins of river valleys. For example, when changing from 5 cm to 1 m 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), the finest 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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Geomorphic process from topographic form automating the interpretation of repeat survey data in river valleys
Earth Surface Processes and Landforms, 2017Co-Authors: Alan Kasprak, Joshua Caster, Sara Bangen, Joel B SankeyAbstract:The ability to quantify the processes driving Geomorphic Change in river valley margins is vital to geomorphologists seeking to understand the relative role of transport mechanisms (e.g. fluvial, aeolian, and hillslope processes) in landscape dynamics. High-resolution, repeat topographic data are becoming readily available to geomorphologists. By contrasting digital elevation models derived from repeat surveys, the transport processes driving topographic Changes can be inferred, a method termed ‘mechanistic segregation.’ Unfortunately, mechanistic segregation largely relies on subjective and time consuming manual classification, which has implications both for its reproducibility and the practical scale of its application. Here we present a novel computational workflow for the mechanistic segregation of Geomorphic transport processes in geospatial datasets. We apply the workflow to seven sites along the Colorado River in the Grand Canyon, where Geomorphic transport is driven by a diverse suite of mechanisms. The workflow performs well when compared to field observations, with an overall predictive accuracy of 84% across 113 validation points. The approach most accurately predicts Changes due to fluvial processes (100% accuracy) and aeolian processes (96%), with reduced accuracy in predictions of alluvial and colluvial processes (64% and 73%, respectively). Our workflow is designed to be applicable to a diversity of river systems and will likely provide a rapid and objective understanding of the processes driving Geomorphic Change at the reach and network scales. We anticipate that such an understanding will allow insight into the response of Geomorphic transport processes to external forcings, such as shifts in climate, land use, or river regulation, with implications for process-based river management and restoration. Copyright © 2017 John Wiley & Sons, Ltd.
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quantifying Geomorphic Change at ephemeral stream restoration sites using a coupled model approach
Geomorphology, 2017Co-Authors: Laura M Norman, Joel B Sankey, David J Dean, Joshua Caster, Stephen B Delong, Whitney M Delong, Jon D PelletierAbstract:Abstract Rock-detention structures are used as restoration treatments to engineer ephemeral stream channels of southeast Arizona, USA, to reduce streamflow velocity, limit erosion, retain sediment, and promote surface-water infiltration. Structures are intended to aggrade incised stream channels, yet little quantified evidence of efficacy is available. The goal of this 3-year study was to characterize the Geomorphic impacts of rock-detention structures used as a restoration strategy and develop a methodology to predict the associated Changes. We studied reaches of two ephemeral streams with different watershed management histories: one where thousands of loose-rock check dams were installed 30 years prior to our study, and one with structures constructed at the beginning of our study. The methods used included runoff, sediment transport, and Geomorphic modelling and repeat terrestrial laser scanner (TLS) surveys to map landscape Change. Where discharge data were not available, event-based runoff was estimated using KINEROS2, a one-dimensional kinematic-wave runoff and erosion model. Discharge measurements and estimates were used as input to a two-dimensional unsteady flow-and-sedimentation model (Nays2DH) that combined a gridded flow, transport, and bed and bank simulation with Geomorphic Change. Through comparison of consecutive DEMs, the potential to substitute uncalibrated models to analyze stream restoration is introduced. We demonstrate a new approach to assess hydraulics and associated patterns of aggradation and degradation resulting from the construction of check-dams and other transverse structures. Notably, we find that stream restoration using rock-detention structures is effective across vastly different timescales.
Alan Kasprak - One of the best experts on this subject based on the ideXlab platform.
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The effects of topographic surveying technique and data resolution on the detection and interpretation of Geomorphic Change
Geomorphology, 2019Co-Authors: Alan Kasprak, Joel B Sankey, Joshua Caster, Nathaniel D. Bransky, Temuulen T. SankeyAbstract: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 5 cm to 1 m among all sites. Coarser resolution data tended to affect interpretation of landscape Change along the margins of river valleys. For example, when changing from 5 cm to 1 m 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), the finest 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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Geomorphic process from topographic form automating the interpretation of repeat survey data in river valleys
Earth Surface Processes and Landforms, 2017Co-Authors: Alan Kasprak, Joshua Caster, Sara Bangen, Joel B SankeyAbstract:The ability to quantify the processes driving Geomorphic Change in river valley margins is vital to geomorphologists seeking to understand the relative role of transport mechanisms (e.g. fluvial, aeolian, and hillslope processes) in landscape dynamics. High-resolution, repeat topographic data are becoming readily available to geomorphologists. By contrasting digital elevation models derived from repeat surveys, the transport processes driving topographic Changes can be inferred, a method termed ‘mechanistic segregation.’ Unfortunately, mechanistic segregation largely relies on subjective and time consuming manual classification, which has implications both for its reproducibility and the practical scale of its application. Here we present a novel computational workflow for the mechanistic segregation of Geomorphic transport processes in geospatial datasets. We apply the workflow to seven sites along the Colorado River in the Grand Canyon, where Geomorphic transport is driven by a diverse suite of mechanisms. The workflow performs well when compared to field observations, with an overall predictive accuracy of 84% across 113 validation points. The approach most accurately predicts Changes due to fluvial processes (100% accuracy) and aeolian processes (96%), with reduced accuracy in predictions of alluvial and colluvial processes (64% and 73%, respectively). Our workflow is designed to be applicable to a diversity of river systems and will likely provide a rapid and objective understanding of the processes driving Geomorphic Change at the reach and network scales. We anticipate that such an understanding will allow insight into the response of Geomorphic transport processes to external forcings, such as shifts in climate, land use, or river regulation, with implications for process-based river management and restoration. Copyright © 2017 John Wiley & Sons, Ltd.
Joshua Caster - One of the best experts on this subject based on the ideXlab platform.
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The effects of topographic surveying technique and data resolution on the detection and interpretation of Geomorphic Change
Geomorphology, 2019Co-Authors: Alan Kasprak, Joel B Sankey, Joshua Caster, Nathaniel D. Bransky, Temuulen T. SankeyAbstract: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 5 cm to 1 m among all sites. Coarser resolution data tended to affect interpretation of landscape Change along the margins of river valleys. For example, when changing from 5 cm to 1 m 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), the finest 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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Geomorphic process from topographic form automating the interpretation of repeat survey data in river valleys
Earth Surface Processes and Landforms, 2017Co-Authors: Alan Kasprak, Joshua Caster, Sara Bangen, Joel B SankeyAbstract:The ability to quantify the processes driving Geomorphic Change in river valley margins is vital to geomorphologists seeking to understand the relative role of transport mechanisms (e.g. fluvial, aeolian, and hillslope processes) in landscape dynamics. High-resolution, repeat topographic data are becoming readily available to geomorphologists. By contrasting digital elevation models derived from repeat surveys, the transport processes driving topographic Changes can be inferred, a method termed ‘mechanistic segregation.’ Unfortunately, mechanistic segregation largely relies on subjective and time consuming manual classification, which has implications both for its reproducibility and the practical scale of its application. Here we present a novel computational workflow for the mechanistic segregation of Geomorphic transport processes in geospatial datasets. We apply the workflow to seven sites along the Colorado River in the Grand Canyon, where Geomorphic transport is driven by a diverse suite of mechanisms. The workflow performs well when compared to field observations, with an overall predictive accuracy of 84% across 113 validation points. The approach most accurately predicts Changes due to fluvial processes (100% accuracy) and aeolian processes (96%), with reduced accuracy in predictions of alluvial and colluvial processes (64% and 73%, respectively). Our workflow is designed to be applicable to a diversity of river systems and will likely provide a rapid and objective understanding of the processes driving Geomorphic Change at the reach and network scales. We anticipate that such an understanding will allow insight into the response of Geomorphic transport processes to external forcings, such as shifts in climate, land use, or river regulation, with implications for process-based river management and restoration. Copyright © 2017 John Wiley & Sons, Ltd.
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quantifying Geomorphic Change at ephemeral stream restoration sites using a coupled model approach
Geomorphology, 2017Co-Authors: Laura M Norman, Joel B Sankey, David J Dean, Joshua Caster, Stephen B Delong, Whitney M Delong, Jon D PelletierAbstract:Abstract Rock-detention structures are used as restoration treatments to engineer ephemeral stream channels of southeast Arizona, USA, to reduce streamflow velocity, limit erosion, retain sediment, and promote surface-water infiltration. Structures are intended to aggrade incised stream channels, yet little quantified evidence of efficacy is available. The goal of this 3-year study was to characterize the Geomorphic impacts of rock-detention structures used as a restoration strategy and develop a methodology to predict the associated Changes. We studied reaches of two ephemeral streams with different watershed management histories: one where thousands of loose-rock check dams were installed 30 years prior to our study, and one with structures constructed at the beginning of our study. The methods used included runoff, sediment transport, and Geomorphic modelling and repeat terrestrial laser scanner (TLS) surveys to map landscape Change. Where discharge data were not available, event-based runoff was estimated using KINEROS2, a one-dimensional kinematic-wave runoff and erosion model. Discharge measurements and estimates were used as input to a two-dimensional unsteady flow-and-sedimentation model (Nays2DH) that combined a gridded flow, transport, and bed and bank simulation with Geomorphic Change. Through comparison of consecutive DEMs, the potential to substitute uncalibrated models to analyze stream restoration is introduced. We demonstrate a new approach to assess hydraulics and associated patterns of aggradation and degradation resulting from the construction of check-dams and other transverse structures. Notably, we find that stream restoration using rock-detention structures is effective across vastly different timescales.
Kristen L. Cook - One of the best experts on this subject based on the ideXlab platform.
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An evaluation of the effectiveness of low-cost UAVs and structure from motion for Geomorphic Change detection
Geomorphology, 2017Co-Authors: Kristen L. CookAbstract:The measurement of topography and of topographic Change is essential for the study of many Geomorphic processes. In recent years, structure from motion (SfM) techniques applied to photographs taken by camera-equipped unmanned aerial vehicles (UAVs) has become a powerful new tool for the generation of high resolution topography. The variety of available UAV systems continues to increase rapidly, but it is not clear whether increased UAV sophistication translates into improved quality of the calculated topography. To evaluate the lower end of the UAV spectrum, a simple low cost UAV was deployed to calculate high resolution topography in the Daan River gorge in western Taiwan, a site with a complicated 3D morphology and a wide range of surface types, making it a challenging site for topographic measurement. Terrestrial lidar surveys were conducted in parallel with UAV surveys in both June and November 2014, enabling an assessment of the reliability of the UAV survey to detect Geomorphic Changes in the range of 30 cm to several meters. A further UAV survey was conducted in June 2015 in order to quantify Changes resulting from the 2015 spring monsoon. To evaluate the accuracy of the UAV derived topography, it was compared to terrestrial lidar data collected during the same survey period using the cloud-to-cloud comparison algorithm M3C2. The UAV-generated point clouds match the lidar point clouds well, with RMS errors of 30–40 cm; however, the accuracy of the SfM point clouds depends strongly on the characteristics of the surface being considered, with vegetation, water, and small scale texture causing inaccuracies. The lidar and SfM data yield similar maps of Change from June to November 2014, with the same areas of Geomorphic Change detected by both methods. The SfM-generated Change map for November 2014 to June 2015 indicates that the 2015 spring monsoon caused erosion throughout the gorge and highlights the importance of event-driven erosion in the Daan River. The results suggest that even very basic UAVs can yield data suitable for measuring Geomorphic Change on the scale of a channel reach.
Issac Stiller - One of the best experts on this subject based on the ideXlab platform.
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Monitoring gully Change: A comparison of airborne and terrestrial laser scanning using a case study from Aratula, Queensland
Geomorphology, 2017Co-Authors: Nicholas R. Goodwin, John Armston, Jasmine Muir, Issac StillerAbstract:Abstract Airborne laser scanning (ALS) and terrestrial laser scanning (TLS) technologies capture spatially detailed estimates of surface topography and when collected multi-temporally can be used to assess Geomorphic Change. The sensitivity and repeatability of ALS measurements to characterise Geomorphic Change in topographically complex environments such as gullies; however, remains an area lacking quantitative research. In this study, we captured coincident ALS and TLS datasets to assess their ability and synergies to detect Geomorphic Change for a gully located in Aratula, southeast Queensland, Australia. We initially used the higher spatial density and ranging accuracy of TLS to provide an assessment of the Digital Elevation Models (DEM) derived from ALS within a gully environment. Results indicated mean residual errors of 0.13 and 0.09 m along with standard deviation (SD) of residual errors of 0.20 and 0.16 m using pixel sizes of 0.5 and 1.0 m, respectively. The positive mean residual errors confirm that TLS data consistently detected deeper sections of the gully than ALS. We also compared the repeatability of ALS and TLS for characterising gully morphology. This indicated that the sensitivity to detect Change using ALS is substantially lower than TLS, as expected, and that the ALS survey characteristics influence the ability to detect Change. Notably, we found that using one ALS transect (mean density of 5 points / m2) as opposed to three transects increased the SD of residual error by approximately 30%. The supplied classification of ALS ground points was also demonstrated to misclassify gully features as non-ground, with minimum elevation filtering found to provide a more accurate DEM of the gully. The number and placement of terrestrial laser scans were also found to influence the derived DEMs. Furthermore, we applied Change detection using two ALS data captures over a four year period and four TLS field surveys over an eight month period. This demonstrated that ALS can detect large scale erosional Changes with head cutting of gully branches migrating approximately 10 m upslope. In comparison, TLS captured smaller scale intra-annual erosional patterns largely undetectable by the ALS dataset with a large rainfall event coinciding with the highest volumetric Change (net Change > 46 m3). Overall, these findings reaffirm the importance of quantifying DEM errors and demonstrate that ALS is unlikely to detect subtle Geomorphic Changes (