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Abstract. A LiDAR Statistical Barnes Objective Analysis (LiSBOA) for the optimal design of lidar scans and retrieval of the velocity statistical moments is proposed. LiSBOA represents an adaptation of the classical Barnes scheme for the statistical analysis of unstructured experimental data in N-dimensional space, and it is a suitable technique for the evaluation over a structured Cartesian grid of the statistics of scalar fields sampled through scanning lidars. LiSBOA is validated and characterized via a Monte Carlo approach applied to a synthetic velocity field. This revisited theoretical framework for the Barnes objective analysis enables the formulation of guidelines for the optimal design of lidar experiments and efficient application of LiSBOA for the postprocessing of lidar measurements. The optimal design of lidar scans is formulated as a two-cost-function optimization problem, including the minimization of the percentage of the measurement volume not sampled with adequate spatial resolution and the minimization of the error on the mean of the velocity field. The optimal design of the lidar scans also guides the selection of the smoothing parameter and the total number of iterations to use for the Barnes scheme. LiSBOA is assessed against a numerical data set generated using the virtual lidar technique applied to the data obtained from a large eddy simulation (LES). The optimal sampling parameters for a scanning Doppler pulsed wind lidar are retrieved through LiSBOA, and then the estimated statistics are compared with those of the original LES data set, showing a maximum error of about 4 % for both mean velocity and turbulence intensity.
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Handheld lidar as a tool for characterizing wood‐rich river corridors
Abstract Wood accumulations influence geomorphic, hydraulic, and ecologic functions within a river corridor, but characterizing these accumulations presents challenges across a range of field and remote sensing methodologies. We evaluate the ability of handheld lidar scanners, specifically lidar‐scanning capabilities of a fourth‐generation iPad Pro, to collect three‐dimensional wood accumulation data, which can be used to inform measurements of wood volume, porosity, complexity, and roughness. We discuss the potential and limitations of this novel methodology for river research and management. We found that handheld lidar presents a cost‐effective input for data‐processing workflows that field measurements of wood accumulation dimensions cannot as easily replicate including (1) a user‐friendly means of data collection and visualization; (2) accurate comparisons of wood volume over time; (3) integration into workflows to measure porosity parameters; and (4) potential use in informing hydraulic and morphodynamic models. Consideration of study area constraints and intended use of scans are prerequisites to using handheld lidar as an effective tool. We identified some specific limitations of using handheld lidar scanners in wood‐rich river corridors, including (1) scanners perform poorly when wood is under water or surrounded by dense vegetation; (2) scanners require physical access to areas of interest at distances less than 5 m; (3) scans need to be manually georeferenced; and (4) scans require manual measurements for any dimensional data, which still have associated user time and error. Handheld lidar as a scientific tool is rapidly developing and there is substantial room for expansion of applications, utilization, and advances in the use of this tool in river research and management.
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- PAR ID:
- 10487573
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- River Research and Applications
- Volume:
- 40
- Issue:
- 3
- ISSN:
- 1535-1459
- Format(s):
- Medium: X Size: p. 353-364
- Size(s):
- p. 353-364
- Sponsoring Org:
- National Science Foundation
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