Absolute Accuracy
Absolute accuracy is an evaluation of how well the measurements (LiDAR Points) of a dataset align with the true or accepted real values. The true values for a project area/datum are generally established by some source of known higher accuracy, such as a professional land survey. LiDAR is considered a digital elevation data source, and thus commonly evaluated against truth points in the vertical direction only.
Absolute accuracy results are highly influenced by these factors:
Reference station coordinate accuracy
Processing workflow & method of evaluation
Systemic calibration (lever arms & boresight)
Measuring Absolute Accuracy
A comparison to surveyed checkpoint.
Only hard surface checkpoints are utilized.
At least 20 checkpoints are considered.
Outliers are only removed in the cases where they are obstructed by a vehicle or other non-permanent object.
Then interpolating LiDAR elevation values from an TIN model
LiDAR FOV is set to 90 degree max (or less depending on the scanner’s max FOV)
TIN model based on all points except distant isolated noise (birds and pits) that get caught in an isolated points filter
The difference between interpolated value and the surveyed checkpoint’s elevation is computed.
Finally summarizing the dataset by using those differences to determine RMSEz.
Measuring absolute accuracy, as opposed to relative accuracy or precision, requires the use of additional data in the form of well distributed independent checkpoints, with accuracy 3x that of the LiDAR data under evaluation. Please refer to the ASPRS standards for full details of control & checkpoint requirements for data processing and reporting, or Phoenix LiDAR’s Survey Ground Control Recommendations document for an overview. These independent checkpoints are vital to the absolute accuracy assessment.
ASPRS method for actually performing the evaluation is through interpolation of elevation values from a TIN or DEM surface.
At surveyed X,Y locations the LiDAR TIN should be sampled and elevation values compared.
They do not give many specifics about how the surface should be constructed.
There are many ways of looking at the statistical results in order to assign an accuracy to the LiDAR data, with RMSEz being the most common.
ASPRS Positional Accuracy Standards for Digital Geospatial Data, 2014. http://www.asprs.org/wp-content/uploads/2015/01/ASPRS_Positional_Accuracy_Standards_Edition1_Version100_November2014.pdf
USGS affirms the standards set by ASPRS for surveyed control & checkpoint locations and distribution. They also outline a TIN & DEM evaluation method, with 4 specific values that should be reported.
NVA (Non-Vegetated Vertical Accuracy, see ASPRS) of ground classified LiDAR TIN
VVA (Vegetated Vertical Accuracy, see ASPRS) of ground classified LiDAR TIN
NVA of a final ground surface DEM
VVA of a final ground surface DEM
LiDAR Base Specifications, 2021. rev A. https://www.usgs.gov/core-science-systems/ngp/ss/lidar-base-specification-data-processing-and-handling-requirements#positional-accuracy-validation
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