Performance Considerations for Small-Footprint Topobathymetric LiDAR

Amar Nayegandhi, Manager of Elevation Technologies at Dewberry, posted this article earlier in the week about performance considerations for small-footprint topobathymetric LIDAR and their use of the RIEGL VQ-820-G airborne laser scanner. Enjoy!


A new suite of commercial small-footprint, green-wavelength airborne LiDAR systems are being developed to enable topobathymetric mapping in coastal and riverine environments. These sensors can provide seamless topography across the land-water interface at very high spatial resolution (five to six points per square meter). 

The new LiDAR systems enable numerous applications in coastal and aquatic ecosystems, including floodplain mapping, fisheries management, marine resource and coral reef ecosystem management, storm surge modeling, and storm damage assessment. 

The Role of Water Clarity in Mapping Submerged Topography
Water clarity plays a vital role in the ability of topobathymetric systems to map submerged topography. Compared to traditional bathymetric LiDAR systems, topobathymetric LiDAR uses a low-power laser pulse, resulting in a depth performance between one and two Secchi depth. Traditional bathymetric LiDAR sensors offer up to three Secchi depths, but with a footprint 20 times wider than topobathymetric LiDAR. Small-footprint topobathymetric LiDAR sensors can map submerged topography between 20 to 25 meters in clear water with high reflective bottom (such as sand), but may only map up to two meters in turbid waters. 

Mapping Topobathymetry in Various Riverine Environments
In collaboration with Watershed Sciences, Inc., we used the Riegl VQ-820-G sensor to collect and process topobathymetric data in Sandy River for the Oregon Department of Geology and Mineral Studies. We mapped channel and floodplain morphology and evaluated the effectiveness of new topobathymetric LiDAR technology in a riverine environment. 

The results showed that in more than 83 percent of the channel (a “high confidence” area), bathymetric point density averaged two points per square meter, with water depths ranging from zero to three meters. The remaining 17 percent of the channel (a “low confidence” area) contained water deeper than three meters. In the high confidence area, we compared the LiDAR measurements with 303 channel points acquired using GPS-based techniques along channel cross sections. The bathymetric accuracy was assessed at 18.4 centimeters RMSE. 

These results suggest that topobathymetric LiDAR is a viable solution to mapping channel and floodplain morphology at Sandy River for ongoing monitoring studies to understand the impacts of the 2007 Marmot Dam removal on downstream morphology and fish habitat. 

New commercial small-print, green-wavelength airborne LiDAR systems are being developed to enable topo-bathymetric mapping in coastal environments. Our DLP software makes topo-bathy processing commercially viable by automating several processes.

The image of the left shows the mouth of the Sandy River flowing into the Columbia River. Using the Riegl VQ-820-G sensor, we obtained a seamless topobathymetric Digital Elevation Model (DEM) of the same area—water depths ranging from zero to three meters. 

Commercializing Small-Footprint Topobathymetric LiDAR
The commercialization of small-footprint topobathymetric LiDAR has opened the possibility of high-resolution seamless topography and bathymetry in coastal and riverine environments. The applications of these data are endless and there is a lot of excitement within the geospatial community on the use of this technology. However, it’s important to understand the technology’s limitations and the conditions that will enable a successful survey. Water clarity and bottom reflectivity play a very important role. Knowledge of the LiDAR sensor and production process is crucial to a successful topobathy dataset. 

At Dewberry, we’re at the forefront of this new commercial technology with successful completion of three recent topobathymetric projects, such as Sandy River, using the Riegl VQ-820-G sensor.



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