Topo-Bathymetric LiDAR for Monitoring River Morphodynamics and Instream Habitats—A Case Study at the Pielach River

Abstract

Airborne LiDAR Bathymetry (ALB) has been rapidly evolving in recent years and now allows fluvial topography to be mapped in high resolution (>20 points/m 2 ) and height accuracy (<10 cm) for both the aquatic and the riparian area. This article presents methods for enhanced modeling and monitoring of instream meso-and microhabitats based on multitemporal data acquisition. This is demonstrated for a near natural reach of the Pielach River, with data acquired from April 2013 to October 2014, covering two flood events. In comparison with topographic laser scanning, ALB requires a number of specific processing steps. We present, firstly, a novel approach for modeling the water surface in the case of sparse water surface echoes and, secondly, a strategy for improved filtering and modeling of the Digital Terrain Model of the Watercourse (DTM-W). Based on the multitemporal DTM-W we discuss the massive changes of the fluvial topography exhibiting deposition/erosion of 10 3 m 3 caused by the 30-years flood event in May 2014.Furthermore, for the first time, such a high-resolution data source is used for monitoring of hydro-morphological units (mesohabitat scale) including the consequences for the target fish species nase (Chondrostoma nasus, microhabitat scale). The flood events caused a spatial Remote Sens. 2015, 7 6161 displacement of the hydro-morphological units but did not effect their overall frequency distribution, which is considered an important habitat feature as it documents resilience against disturbances.

Water Surface Reconstruction in Airborne Laser Bathymetry From Redundant Bed Observations

“…As stated earlier, the reference water surface model was obtained from the IR water surface returns. The modeled surfaces, in turn, are interpolated from the estimated water level heights along the river axis using the approach described in Mandlburger et al (2015a). Potential tilts of the water surface perpendicular to the flow direction are hereby neglected.…”

“…Using the semi-automatic approach described in Mandlburger et al (2015a), an approximated Digital Water-level Model (DWM) is first generated based on linear water surface profiles. A refined DWM (50 cm grid) is interpolated from all IR echoes within a small height tolerance band around the approximate model.…”

“…white parts within the channel in Figure 5). For more details about the study area please refer to Mandlburger et al (2015a) and the cited literature therein. Data acquisition was carried out with the RIEGL VQ-880-G topobathymetric laser scanner mounted in the nose pod of a Diamond DA42 light aircraft from 600 m above ground level on June, 16, 2016.…”

Point Distribution as True Quality of LiDAR Point Cloud

“…Depending on task and applied methods, some features are more essential, that must be considered compliting spatial data acquisition. For example, flood-risk maps (Webster et al, 2004) can be generated using DSM, therefore only laser scanning of terrain is sufficient for research, but bathymetric LiDAR (Mandlburge et al, 2015) may be more suitable for river hydrodinamic system modelling and flood simulation. Speaking about object classification and spatial statistics, the research of Jakubowski et al, related with extraction of forest structure metrics, has showed that methods require a threshold density to achieve reasonable accuracy, but that does not benefit significantly from very high LiDAR density (Jakubowski et al, 2013).…”

“…Data processing experts are mainly associated with digital elevation and surface modeling, which are applied for flood risk and floodplain estimation (Webster et al, 2004), (Casas et al, 2006), (Mandlburge et al, 2015) or road planning . Different experts mention the quality of LiDAR point cloud to generate precise DEMs and DSMs shortly formulating it in high point density (Karel et al, 2006), (Liu et al, 2008), (Zhi and Zhong, 2008).…”