Taming a Wild Survey Environment

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Watershed Sciences Inc. (WSI) is a professional services business with its headquarters located in the lush, green hills of Corvallis, Oregon. WSI focuses on providing survey quality data for businesses and government entities throughout the United States, primarily in the Pacific Northwest. The company provides digital data for its clients in a number of formats, including map data for use in Esri’s ArcGIS platform. A large number of clients–including forestry, state and local governments, and environmental agencies–rely on intelligent geospatial models of the landscape to do their jobs better.

While the Pacific Northwest is known for its expansive evergreen forests, white water rivers, and mountainous regions, the area doesn’t always cooperate with engineers and ecologists looking for an accurate survey of riverine environments. Aerial and satellite imagery cannot penetrate the cloud cover or the thick forest canopy that lends itself to the area’s landscape. Mapping river bottoms using ground- or boat-based methods can be extremely difficult due to remote access and dangerous currents.

To tame this wild survey environment, WSI in cooperation with Amar Nayegandhi from Esri partner Dewberry based in Tampa, Florida tested a Riegl VQ 820-G sensor – an airborne hydrographic laser scanner designed to penetrate water and provide seamless topography between the land and shallow water. WSI performs many waterborne surveys each year for its clients, which can be costly and time-consuming using traditional survey methods. WSI’s team was looking for a sensor with a high pulse rate and small laser footprint to measure relatively narrow stream channels and shallow water areas. "Our traditional focus is streams, fisheries, floodplain modeling, and waterway restoration projects in the region’s inland water systems," said Russ Faux, WSI CEO.

Early on the group was skeptical about how the laser would perform. The Riegl sensor had been demonstrated off the coast of Florida in crystal clear water. "We like a challenge," said Faux. "River systems we are known for surveying have lots of turbidity, white water, and nonreflective river bottoms. We couldn’t help but wonder how it was going to operate in those environments."

Putting LiDAR to the Test
With these concerns in mind, the crew took the laser and tested it on a pilot area located on the Sandy River in Oregon. The Sandy River originates on the slopes of Mount Hood and joins the Columbia River east of Portland. In 2008, Marmot Dam was removed, which has made the river of particular interest to scientists and engineers but also has provided a challenge to collecting river data, as much of the riverbank is inaccessible and the dense forest along the river masks GPS signals.

Using the Riegl VQ-820-G, WSI collected LiDAR data of the river corridor and processed the raw data to create a georeferenced point cloud. The point cloud was then classified to identify water surface, terrain, and river bottom. The classified point cloud was used in ArcGIS employing specialized Python scripting to create a surface model interpretation. The interpretation of this model included depth analysis; statistics; and depth modeling, which was used to understand how far into the water column the laser could penetrate. The surface model and analysis were created using the 3D Analyst and Spatial Analyst extensions for ArcGIS.

The results were encouraging to WSI’s technical team. The ultimate result was 80 percent of the river was confidently mapped with a vertical accuracy of 18 centimeters when compared to independent cross section data collected from field surveys. The 20 percent of the river that was not confidently mapped was attributed to river depth that was too great for the laser to penetrate. The areas of low confidence were easily identified, and a confidence layer was created in ArcGIS to inform the client of areas where depths were indeterminate.

"Many of our clients will perform their own boat-based, sonar surveys," said Colin Cooper, senior research scientist at WSI. "However, it’s hard and often dangerous to get readings all the way to the shoreline. It is difficult to get that final meter or two to the bank’s edge or shallow side channels. With the Riegl sensor, WSI is able to map the near shore and shallow-water environments that many traditional ground-based methods can’t access, and provide seamless data collection with a clear definition of the water’s edge. We give them a seamless surface model that is complete or indicates where deeper waters need to be mapped, ultimately saving time on any ancillary surveys."

Basing a Business on a Beam
WSI is an early adopter of LiDAR technology, deploying its first sensor in 2004. The company began as a research project headed by Faux at Oregon State University in 1999 but quickly spun out on its own and has been doing high-resolution remote sensing and geospatial analysis ever since.

To perform QA/QC checks in this quick-paced environment, staff members’ primary tool is a hillshade created in ArcGIS. This allows them to inspect the quality of the derived models and run spatial statistics. Depth models that include breaklines (i.e., 3D polylines representing the land/water interface, in this case) are also created and inspected in the ArcGIS environment; much of the breakline editing and 3D modeling is inspected for accuracy in a similar manner. "We are primarily working in an Esri environment," said Cooper. "We are always looking at and deriving our data products in ArcGIS, due to the fact that most of our client base does its research in this setting."

WSI’s clients depend on 3D and spatial analysis to analyze stream channel characteristics including cross section profiling, flood inundation, and change detection. The ArcGIS environment has been the standard since the start. Clients use both ArcGIS and toolkits created by Esri partners that analyze rivers in the ArcGIS environment primarily for habitat modeling, geomorphology studies, and restoration projects. The ability to pull a point cloud into a familiar environment and change the point cloud classifications while in that environment has been a big advance. Another bonus is the ability to look at multiple layers of different information–perhaps placing multispectral imagery on top of a digital elevation model (DEM) or point cloud or a polygonal area of confidently mapped areas on top of a DEM. These have always been key components of the ArcGIS environment and continue to be a strength.

Keeping up with Changing Client Requirements
"The nature of mapping has really changed over the last few years," Faux said. "Before, it was mostly ground mapping. Today, clients are expecting fully classified point clouds and a broader array of derived products and features."

Faux admitted that making these large point clouds of data available to WSI clients is powerful and something that hasn’t been possible for very long. "For years, we scientists and researchers have had high-end computers networked together, so we’ve had the massive processing power required to deal with this data," he said. "But our clients are often on desktops or even mobile devices. Making high-resolution spatial data products available to the end clients in a versatile and familiar environment like ArcGIS is a huge advantage."

While the LAS files–public file formats for the interchange of threedimensional point cloud data–have a lot more information attached to them, it is the derived end products that are used more often by clients to do their mapping and modeling. Using high-resolution terrain models created from the LiDAR data, users have improved 3D visualization power and can create limitless cross sections on demand–a real full-service model. The ability to provide these derived files and manipulate them in ArcGIS has changed how WSI staff gives data to their clients. WSI is now able to fully classify the topography with the bathymetric surface, creating a true, continuous mapped surface.

"The technology and methodology have changed so fast that we are now doing full point cloud classification: buildings, vegetation, power lines, submerged topography–you name it," said Cooper. "We are now literally mapping and integrating everything, truly maximizing the potential that the ArcGIS toolset offers."

Looking Forward with LiDAR
WSI has approached LiDAR from a different angle since the beginning. Instead of simply providing imagery or data, WSI has always focused on the information it can gain from analysis of the remotely sensed data. The company has been deriving slopes, channel widths, riparian community structures, and more–all from LiDAR data–since the start.

New technology continues to introduce ways in which WSI staff members use LiDAR. Shallow-water bathymetric LiDAR is making it possible to support an array of applications including accurate flood modeling, updated tsunami inundation maps, and other hazard assessments. Bathymetric LiDAR sensors are allowing WSI to look more closely at environmental conservation efforts including aquatic habitat assessments and vegetation analyses.

"LiDAR and high-resolution geospatial mapping are really becoming a staple in what people use every day," said Faux. "We are doing high-end work, but technology like iPads and other mobile devices that can display and manipulate this data are providing access so people can use this information more readily than ever before at any time or place." For more information, contact Layne Bennett at lbennett@watershedsciences. com or 541-752-1204.

Karen Richardson is a senior writer at Esri. She covers stories about the use of GIS for creating maps, data and charts including 3D, LiDAR and imagery data.

A 1.500Mb PDF of this article as it appeared in the magazine complete with images is available by clicking HERE