Lidar data and their derivative metrics are fundamental inputs to many areas of scientific research, including flood, erosion, and coastal modeling.
Lidar data and their derivative metrics are fundamental inputs to a host of DOI and USGS scientific contributions, including hydrology, flood modeling, fault detection and geologic mapping, topographic and land-surface mapping, landslide and volcano hazards mapping and monitoring, forest canopy and habitat characterization, coastal and fluvial erosion mapping. Therefore, the quality of lidar data affects the quality of USGS’s scientific contributions in a significant manner. The USGS guidance, among other recommendations, to Core Science Systems recommends the following work:
- Define and conduct lidar research to gather information on the development of new data acquisition instruments.
- Provide cutting edge guidance, specifications, and standards for acquiring and managing lidar data
- Provide consistent, standardized, authoritative lidar source data across the United States via 3DEP with well-documented metadata, and easy-to-use tools to access and work with these data
- Increase the preference to very-large-area, multiple-instrument collections over smaller, county-size lidar collections.
- Provide mechanisms to help calibrate and validate airborne lidar collections, including using survey grade ground-based terrestrial laser scanning data collected by others.
- Develop methods to systematically compare interswath accuracies, and methods to compare adjacent or overlapping lidar data, in order to develop a more seamless 3DEP product and to guarantee the user is getting the best data possible.
Taking cues from the guidance, the RCA-EO conducts cutting edge research on Lidar Data Quality Assurance (QA) and in particular for data collected for the 3D Elevation Program (3DEP). The document is structured into various sections that describe the areas of lidar work. They are:
- Lidar Inter and intra Swath Accuracy Assessment (Relative accuracy)
- 3D Accuracy Assessment
- Assessment of capabilities new technologies (photon counting technologies such as Geiger Mode and Single Photon Lidar, UAVs etc.)
- Total Propagated Uncertainty for Lidar data
- Topobathymetric lidar data quality and capability assessment
ASPRS Guidelines on Geometric Inter-Swath Accuracy and Quality of Lidar Data (March 2018, PERS)
2020 Niobrara River Topobathymetric Lidar Validation – USGS Field Survey Data
Central South Dakota Airborne Lidar Validation - Field Survey Data
Kootenai River Topobathymetric Lidar Validation Survey Data
Absolute accuracy assessment of lidar point cloud using amorphous objects
General external uncertainty models of three-plane intersection point for 3D absolute accuracy assessment of lidar point cloud
ASPRS research on quantifying the geometric quality of lidar data
2020 Niobrara River Topobathymetric Lidar Validation – USGS Field Survey DataU.S. Geological Survey (USGS) scientists conducted field data collection efforts between August 17th and 28th, 2020 over a large stretch of the Niobrara River in Nebraska using high accuracy surveying technologies. The work was initiated as an effort to validate commercially acquired topobathymetric light detection and ranging (lidar) data. The goal was to compare and validate the airborne lidar d
Central South Dakota Airborne Lidar Validation - Field Survey DataU.S. Geological Survey (USGS) scientists conducted field data collection efforts during the time periods of April 25 - 26, 2017, October 24 - 28, 2017, and July 25 - 26, 2018, using a combination of surveying technologies to map and validate topography, structures, and other features at five sites in central South Dakota. The five sites included the Chamberlain Explorers Athletic Complex and the C
Kootenai River Topobathymetric Lidar Validation Survey DataU.S. Geological Survey (USGS) scientists conducted field data collection efforts during the week of September 25 - 29, 2017, using a combination of conventional surveying technologies, for a large stretch of the Kootenai River near Bonners Ferry, Idaho. The work was initiated as an effort to validate commercially acquired topobathymetric light detection and ranging (lidar) data. The goal was to co
Absolute accuracy assessment of lidar point cloud using amorphous objectsThe accuracy assessment of airborne lidar point cloud typically estimates vertical accuracy by computing RMSEz (root mean square error of the z coordinate) from ground check points (GCPs). Due to the low point density of the airborne lidar point cloud, there is often not enough accurate semantic context to find an accurate conjugate point. To advance the accuracy assessment in full three-dimension
General external uncertainty models of three-plane intersection point for 3D absolute accuracy assessment of lidar point cloudThe traditional practice to assess accuracy in lidar data involves calculating RMSEz (root mean square error of the vertical component). Accuracy assessment of lidar point clouds in full 3D (dimension) is not routinely performed. The main challenge in assessing accuracy in full 3D is how to identify a conjugate point of a ground-surveyed checkpoint in the lidar point cloud with the smallest possib
ASPRS research on quantifying the geometric quality of lidar dataThe ASPRS Lidar Cal/Val (calibration/validation) Working Group led by the US Geological Survey (USGS) to establish “Guidelines on Geometric Accuracy and Quality of Lidar Data” has made excellent progress via regular teleconferences and meetings. The group is focused on identifying data quality metrics and establishing a set of guidelines for quantifying the quality of lidar data. The working group