Editor’s Note: One of our customers, Quantum Spatial, is currently being featured on LiDAR News. Check out the post below or at the LiDAR News website to learn more about Quantum Spatial and their work with RIEGL sensors and systems!

Background

Russ Faux is currently Sr. Vice President for Growth Initiatives at Quantum Spatial, Inc. He has spent most of his 30-year career working with some form of airborne remote sensing and geospatial technologies. In 1998, he founded a small remote sensing company named Watershed Sciences, Inc. (WSI) that focused on water resource applications using thermal infrared imagery and newly emerging digital cameras.

Russ recalls, “WSI purchased its first airborne LiDAR sensor in 2003 after recognizing the tremendous potential the technology offered to the natural resource and engineering communities. WSI introduced 3D laser scanning to many clients that quickly included the Puget Sound and Oregon LiDAR Consortiums.”

Working in partnership with the consortiums, WSI developed LiDAR specifications that maximized the capabilities of the technology in a wide range of applications and was widely adopted as a regional standard. Over the next decade, WSI expanded its LiDAR operations by continuing to invest in new airborne LiDAR technology and developing new applications.

Quantum Spatial, Inc. (QSI) purchased WSI in 2013 to form one of the largest commercial geospatial firms in North America. QSI focuses on the full range of remote sensing and geospatial products extending from the collection and processing of LiDAR and spectral imagery to data analytics and enterprise solutions. In 2017, QSI collected and processed over 139,000 sq. miles of broad area LiDAR and over 27,000 linear miles of corridor LiDAR for a variety of clients and applications.

Hardware and Software

In order to serve a diverse client base, QSI operates a wide variety of LiDAR and imaging sensors to provide the best solution for any given application. In 2017, QSI added the new RIEGL VQ-1560i airborne mapping system to its existing fleet of airborne LiDAR sensors. For smaller areas and corridor applications, QSI utilizes a RIEGL VQ-480i sensor.

QSI also deploys 3D hardware to support a variety of emerging and specialty markets. In 2017, QSI purchased the RIEGL VQ-880-G airborne LiDAR system for shallow-water hydrographic applications. “The new sensor complements our existing RIEGL VQ-820-G topo-bathymetric sensor that we fielded in 2013 to collect critical elevation data in near shore and shallow riverine environments,” Russ noted. He continued, “QSI also works extensively with very high-density point clouds collected through project partners (or clients) deploying the RIEGL VUX series sensors on UAV and/or helicopter platforms.”

The software tools for processing of 3D data have evolved rapidly. Workflows are customized for the specific sensor and application. In general, QSI utilizes vendor – specific software for creation of the geo-referenced point clouds, but they typically move to a combination of third-party software (such as Terrasolid) for base level processing, point editing, and creation of standard elevation products such as a DTM.

They utilize software tools such as ESRI ArcGIS and Applied Imagery QT Modeler for a variety of quality control, visualization, and product generation functions. In addition, QSI continues to develop customized tools and workflows that are designed for extracting specific features and data analytics from the LiDAR point clouds and other co-registered data sources.

Evaluating Technology

QSI evaluates new technology and products as they enter the market, regardless of vendor. The focus is invariably to provide higher value to their clients and to discover how state-of-the-art technologies can be used to develop new solutions and applications. RIEGL’s introduction of the VQ-1560i system was particularly appealing since QSI frequently tackles projects in the Mountain West and Alaska that require collection of high density data (USGS QL1 or better) in rugged and heavily forested environments.

The VQ-1560i’s multiple time around (MTA) technology and high pulse rate, dual-channel laser system significantly increased collection efficiencies in mountainous terrain over existing sensors without compromising precision or quality. “The RIEGL VQ-1560i system built upon this concept while providing a two-fold increase in data acquisition efficiency. QSI recognized the value that fielding the RIEGL VQ-1560i could bring to our client base,” Russ explained.

QSI entered the shallow-water topo-bathymetric LiDAR market to address the needs of clients that required a reliable method to collect accurate elevation data in the near-shore, back-bay, estuary, and riverine environments. After evaluating products that were on the market, QSI was attracted to the RIEGL VQ-880-G system because of the high pulse-rate combined with a narrow beam divergence. This enabled QSI to map complex aquatic environments at data densities that rivaled more traditional terrestrial sensors. These densities provided increased opportunity for data interpretation and extraction of aquatic features that were important to many stream restoration and coastal resiliency projects.

Workflow Integration

QSI has decades of experience acquiring and processing 3D data from a variety of sensors. Accordingly, the internal workflows are sensor agnostic once a calibrated point cloud is created. QSI has application-specific workflows that are based on a combination of third-party software and internally developed programs.

The RIEGL processing software suite (RiPROCESS, RiANALYZE / SDCImport, and RiWORLD) is used to read the raw laser scanner data and apply sensor orientation and positioning information to generate a calibrated point cloud. QSI integrates additional RIEGL products such as RiHYDRO for bathymetric data processing as additional steps in their workflows when doing more specific processing functions to meet the project needs. QSI’s experience in developing LiDAR-derived products, combined with RIEGL’s history of developing LiDAR sensors and software products, allows for fairly quick adoption of new products and customization of workflows.

Project Experience

Since taking delivery of the VQ-1560i last December (2017), QSI has deployed the sensor on several challenging LiDAR projects in the mountainous terrain of the Pacific Northwest. One ongoing project is the collection of QL1 LiDAR data over ~5,018 sq. miles of Washington’s Olympic Peninsula for the Washington Department of Natural Resources, WA Geological Survey, and the USGS 3DEP Program. The data will be used for multiple applications including geologic hazard mapping, conservation planning, floodplain mapping, hydrologic modeling, forest health, and engineering design.

In accordance with USGS specifications, data collection is required during the leaf-off season when extended periods of rain and low clouds are common in the region. The use of the VQ-1560i system enables QSI to maximize acquisition during narrow and precious weather windows by providing a 3X efficiency gain over their previous generation of LiDAR sensors. In addition, the temperate rain forests found on the Olympic Peninsula provide a challenge in obtaining the ground returns needed to generate a quality bare earth elevation model. “In this situation, the VQ-1560i’s use of linear-mode technology and on-line waveform analysis increases the probability of reliable ground returns under the forest canopy,” Russ noted.

QSI recently completed a topo-bathymetric LiDAR project on 161 miles of the Willamette River in Oregon using the RIEGL VQ-880-G system. The project was done in cooperation with the US Army Corps of Engineers and the USGS to support a wide variety of applications including anadromous fish passage and floodplain management.

The Willamette River has a relatively complex floodplain with numerous side channels and sloughs that represent important habitat for fish. The RIEGL VQ-880-G was the ideal system for this project since its high pulse rate (point density = 20 ppm) and small foot print (beam divergence) were able to capture detail in the small, off-channel areas that were important to this study.

Russ noted, “On this project, the VQ-880-G was able to capture continuous depths down to about 2m and captured areas that were not possible from ground or water-based surveys. The topo-bathymetric LiDAR data will be integrated with boat-based sonar in the deeper parts of the channel to create a continuous elevation model.”

Return on Investment

QSI can analyze return-on-investment (ROI) differently, depending on the market and application. The most straightforward way is to evaluate efficiency improvements using new hardware/software compared to existing technology considering the same specifications and quality standards. As previously mentioned, the RIEGL VQ-1560i represented an improvement in data collection efficiency of 2-4X (depending on terrain and quality level) while preserving high levels of accuracy and precision. Efficiency improvements not only reduce flight and field expenses, but extend to fewer missions and typically reduced processing time.

Another way to address ROI is the ability to utilize hardware/software to develop new products and applications. For example, the ability to collect shallow-water topo-bathymetric LiDAR created new opportunities for mapping near-shore coastal and complex riverine environments that are critically important for applications such as flood inundation modeling, habitat assessment, and coastal resiliency. “The ability to collect detailed elevation data were not possible or practical before the introduction of new and innovative sensors,” Russ explained.

Looking to the Future

“In recent years, the demand for 3D data has continued to increase and the dominant trend is for higher resolution and accuracy,” Russ pointed out. He continued, “New sensor technologies and cloud-based computing systems allow us to collect, process, and quickly analyze point cloud data at scales and densities that were barely imaginable a few years ago. This trend is opening up new applications as clients increasingly realize the value of these data across a spectrum of applications from monitoring geologic processes to inspecting critical infrastructure.”