Abstract
Lidar remote sensing has been used to survey stream channel and floodplain topography for decades. However, traditional platforms, such as aerial laser scanning (ALS) from an airplane, have limitations including flight altitude and scan angle that prevent the scanner from collecting a complete survey of the riverscape. Drone laser scanning (DLS) or unmanned aerial vehicle (UAV)-based lidar offer ways to scan riverscapes with many potential advantages over ALS. We compared point clouds and lidar data products generated with both DLS and ALS for a small gravel-bed stream, Stroubles Creek, located in Blacksburg, VA. Lidar data points were classified as ground and vegetation, and then rasterized to produce digital terrain models (DTMs) representing the topography and canopy height models (CHMs) representing the vegetation. The results highlighted that the lower-altitude, higher-resolution DLS data were more capable than ALS of providing details of the channel profile as well as detecting small vegetation on the floodplain. The greater detail gained with DLS will provide fluvial researchers with better estimates of the physical properties of riverscape topography and vegetation.
Highlights
Riverscapes are complex, interconnected ecosystems consisting of channels, banks, riparian zones, and floodplains [1]
We presented a methodology for using drone-based laser scanning to survey riverscapes and simple workflows for processing the resulting data
The results from this study show that these workflows can be effectively applied using a standard laptop computer to process drone laser scanning (DLS) datasets that are 100 times the point density of aerial laser scanning (ALS)
Summary
Riverscapes are complex, interconnected ecosystems consisting of channels, banks, riparian zones, and floodplains [1]. Biotic communities and ecosystem processes are strongly responsive to the physical aspects of riverscapes. The quantification of these physical properties depends on timeand space-varying parameters, such as inundated surface area, riparian structure, streambed habitat complexity, and turbulence within the water column, as well as at the sediment–water and water–air interfaces. Some studies represent riverscape habitat complexity through the spatial variability of the environment. This variability can be defined by various metrics including topographic roughness [3], hydraulic roughness [4], topographic complexity [5], or hydraulic complexity [6]
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