Channel Morphology Change after Restoration: Drone Laser Scanning versus Traditional Surveying Techniques
| dc.contributor.author | Resop, Jonathan P. | en |
| dc.contributor.author | Hendrix, Coral | en |
| dc.contributor.author | Wynn-Thompson, Theresa | en |
| dc.contributor.author | Hession, W. Cully | en |
| dc.date.accessioned | 2024-04-29T13:25:46Z | en |
| dc.date.available | 2024-04-29T13:25:46Z | en |
| dc.date.issued | 2024-04-10 | en |
| dc.date.updated | 2024-04-26T13:08:59Z | en |
| dc.description.abstract | Accurate and precise measures of channel morphology are important when monitoring a stream post-restoration to determine changes in stability, water quality, and aquatic habitat availability. Practitioners often rely on traditional surveying methods such as a total station for measuring channel metrics (e.g., cross-sectional area, width, depth, and slope). However, these methods have limitations in terms of coarse sampling densities and time-intensive field efforts. Drone-based lidar or drone laser scanning (DLS) provides much higher resolution point clouds and has the potential to improve post-restoration monitoring efforts. For this study, a 1.3-km reach of Stroubles Creek (Blacksburg, VA, USA), which underwent a restoration in 2010, was surveyed twice with a total station (2010 and 2021) and twice with DLS (2017 and 2021). The initial restoration was divided into three treatment reaches: T1 (livestock exclusion), T2 (livestock exclusion and bank treatment), and T3 (livestock exclusion, bank treatment, and inset floodplain). Cross-sectional channel morphology metrics were extracted from the 2021 DLS scan and compared to metrics calculated from the 2021 total station survey. DLS produced 6.5 times the number of cross sections over the study reach and 8.8 times the number of points per cross section compared to the total station. There was good agreement between the metrics derived from both surveying methods, such as channel width (R<sup>2</sup> = 0.672) and cross-sectional area (R<sup>2</sup> = 0.597). As a proof of concept to demonstrate the advantage of DLS over traditional surveying, 0.1 m digital terrain models (DTMs) were generated from the DLS data. Based on the drone lidar data, from 2017 to 2021, treatment reach T3 showed the most stability, in terms of the least change and variability in cross-sectional metrics as well as the least erosion area and volume per length of reach. | en |
| dc.description.version | Published version | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Resop, J.P.; Hendrix, C.; Wynn-Thompson, T.; Hession, W.C. Channel Morphology Change after Restoration: Drone Laser Scanning versus Traditional Surveying Techniques. Hydrology 2024, 11, 54. | en |
| dc.identifier.doi | https://doi.org/10.3390/hydrology11040054 | en |
| dc.identifier.uri | https://hdl.handle.net/10919/118694 | en |
| dc.language.iso | en | en |
| dc.publisher | MDPI | en |
| dc.rights | Creative Commons Attribution 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en |
| dc.subject | stream restoration | en |
| dc.subject | channel morphology | en |
| dc.subject | lidar | en |
| dc.subject | surveying | en |
| dc.subject | drone laser scanning | en |
| dc.subject | UAVs | en |
| dc.title | Channel Morphology Change after Restoration: Drone Laser Scanning versus Traditional Surveying Techniques | en |
| dc.title.serial | Hydrology | en |
| dc.type | Article - Refereed | en |
| dc.type.dcmitype | Text | en |