CompassData Calibration for LiDAR Evaluation, Testing and Boresighting
LiDAR analysis is a growing need in the GIS community and CompassData is at the cutting edge of this field.
Ground Truth
CompassData establishes and manages multi-use GPS calibration sites for digital sensors and LiDAR, working with clients such as the National Oceanic and Atmospheric Administration (NOAA) and the United States Geological Survey (USGS).
Manual Editing/Post-processing
Besides providing the GPS and Control necessary to ensure "Ground Truth" for LiDAR projects, CompassData's team includes post-processing professionals who have the expertise to ensure Quality Control/Quality Assurance for LiDAR deliverables.
Postprocessing from CompassData includes GPS and IMU data, in a LiDAR LAS file. This includes all relevant LiDAR attributes: classification, intensity, return information, GPS timestamp, flight line information, etc.
QA/QC for LiDAR
Quantitative for vertical accuracy, horizontal accuracy, clustering of points and nominal posting
Qualitative for the elevation surface (look and feel) and removal of anomalies or temporary features such as vehicles; intersecting building corners; assessing completeness; etc.
- FEMA PM61 Compliant (FEMA Procedure Memorandum No. 61: "Standarads for LiDAR and Other High Quality Digital Topography" published Sept. 27, 2010)
- USGS V13 Compliant (United States Geological Survey (USGS) LiDAR Guidelines and Base Specifications Version 13)
LiDAR Glossary:
Digital Surface Model (DSM): Elevation model including ground, vegetation, buildings and other objects
Digital Elevation Model (DEM): Elevation model including ground but not vegetation, buildings or other objects
Digital Terrain Model (DTM): Elevation model including ground and break line but not vegetation, buildings or other objects
Nominal Post Spacing (NPS): Average distance between adjacent LiDAR points (ft or m)
Point Density: Number of LiDAR points per unit area (points per square meter)
Root Mean Square Error (RMSE): Statistical value equal to the square root of the average of the squares of the differences between known points and modeled points in the LiDAR surface
Vertical Accuracy of LiDAR: is not an "absolute" accuracy. It is commonly specified as the Root Mean Square Error (RMSEz)
- RMSEz is 68% confidence interval
- RMSEz x 1.96 is the 95% confidence interval
- RMSEz is the 99.7% confidence interval
