Quantifying the Spatial Variability of Annual and Seasonal Changes in Riverscape Vegetation Using Drone Laser Scanning

Riverscapes are complex ecosystems consisting of dynamic processes influenced by spatially heterogeneous physical features. A critical component of riverscapes is vegetation in the stream channel and floodplain, which influences flooding and provides habitat. Riverscape vegetation can be highly vari...

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Main Authors: Jonathan P. Resop, Laura Lehmann, W. Cully Hession
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Drones
Subjects:
Online Access:https://www.mdpi.com/2504-446X/5/3/91
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author Jonathan P. Resop
Laura Lehmann
W. Cully Hession
author_facet Jonathan P. Resop
Laura Lehmann
W. Cully Hession
author_sort Jonathan P. Resop
collection DOAJ
description Riverscapes are complex ecosystems consisting of dynamic processes influenced by spatially heterogeneous physical features. A critical component of riverscapes is vegetation in the stream channel and floodplain, which influences flooding and provides habitat. Riverscape vegetation can be highly variable in size and structure, including wetland plants, grasses, shrubs, and trees. This vegetation variability is difficult to precisely measure over large extents with traditional surveying tools. Drone laser scanning (DLS), or UAV-based lidar, has shown potential for measuring topography and vegetation over large extents at a high resolution but has yet to be used to quantify both the temporal and spatial variability of riverscape vegetation. Scans were performed on a reach of Stroubles Creek in Blacksburg, VA, USA six times between 2017 and 2019. Change was calculated both annually and seasonally over the two-year period. Metrics were derived from the lidar scans to represent different aspects of riverscape vegetation: height, roughness, and density. Vegetation was classified as scrub or tree based on the height above ground and 604 trees were manually identified in the riverscape, which grew on average by 0.74 m annually. Trees had greater annual growth and scrub had greater seasonal variability. Height and roughness were better measures of annual growth and density was a better measure of seasonal variability. The results demonstrate the advantage of repeat surveys with high-resolution DLS for detecting seasonal variability in the riverscape environment, including the growth and decay of floodplain vegetation, which is critical information for various hydraulic and ecological applications.
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spelling doaj.art-090d4a22fe8940149b33c13d364511a62023-11-22T12:43:16ZengMDPI AGDrones2504-446X2021-09-01539110.3390/drones5030091Quantifying the Spatial Variability of Annual and Seasonal Changes in Riverscape Vegetation Using Drone Laser ScanningJonathan P. Resop0Laura Lehmann1W. Cully Hession2Department of Geographical Sciences, University of Maryland, College Park, MD 20740, USADepartment of Biological Systems Engineering, Virginia Tech, Blacksburg, VA 24060, USADepartment of Biological Systems Engineering, Virginia Tech, Blacksburg, VA 24060, USARiverscapes are complex ecosystems consisting of dynamic processes influenced by spatially heterogeneous physical features. A critical component of riverscapes is vegetation in the stream channel and floodplain, which influences flooding and provides habitat. Riverscape vegetation can be highly variable in size and structure, including wetland plants, grasses, shrubs, and trees. This vegetation variability is difficult to precisely measure over large extents with traditional surveying tools. Drone laser scanning (DLS), or UAV-based lidar, has shown potential for measuring topography and vegetation over large extents at a high resolution but has yet to be used to quantify both the temporal and spatial variability of riverscape vegetation. Scans were performed on a reach of Stroubles Creek in Blacksburg, VA, USA six times between 2017 and 2019. Change was calculated both annually and seasonally over the two-year period. Metrics were derived from the lidar scans to represent different aspects of riverscape vegetation: height, roughness, and density. Vegetation was classified as scrub or tree based on the height above ground and 604 trees were manually identified in the riverscape, which grew on average by 0.74 m annually. Trees had greater annual growth and scrub had greater seasonal variability. Height and roughness were better measures of annual growth and density was a better measure of seasonal variability. The results demonstrate the advantage of repeat surveys with high-resolution DLS for detecting seasonal variability in the riverscape environment, including the growth and decay of floodplain vegetation, which is critical information for various hydraulic and ecological applications.https://www.mdpi.com/2504-446X/5/3/91UAVslidarstreamscanopy heightroughnessvegetation density
spellingShingle Jonathan P. Resop
Laura Lehmann
W. Cully Hession
Quantifying the Spatial Variability of Annual and Seasonal Changes in Riverscape Vegetation Using Drone Laser Scanning
Drones
UAVs
lidar
streams
canopy height
roughness
vegetation density
title Quantifying the Spatial Variability of Annual and Seasonal Changes in Riverscape Vegetation Using Drone Laser Scanning
title_full Quantifying the Spatial Variability of Annual and Seasonal Changes in Riverscape Vegetation Using Drone Laser Scanning
title_fullStr Quantifying the Spatial Variability of Annual and Seasonal Changes in Riverscape Vegetation Using Drone Laser Scanning
title_full_unstemmed Quantifying the Spatial Variability of Annual and Seasonal Changes in Riverscape Vegetation Using Drone Laser Scanning
title_short Quantifying the Spatial Variability of Annual and Seasonal Changes in Riverscape Vegetation Using Drone Laser Scanning
title_sort quantifying the spatial variability of annual and seasonal changes in riverscape vegetation using drone laser scanning
topic UAVs
lidar
streams
canopy height
roughness
vegetation density
url https://www.mdpi.com/2504-446X/5/3/91
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AT lauralehmann quantifyingthespatialvariabilityofannualandseasonalchangesinriverscapevegetationusingdronelaserscanning
AT wcullyhession quantifyingthespatialvariabilityofannualandseasonalchangesinriverscapevegetationusingdronelaserscanning