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