Project Report

Spatial Fuser Pipeline Name

The LiDARMill Spatial Fuser project report is intended for data end users to review details of how mission data was acquired and processed, as both methodologies directly impact the accuracy and quality of the resulting data products generated.

Overview

Time

Time	Local	UTC
Data Acquisition	Local Date and Time of data acquisition (time zone deduced using rover location)	UTC Date and Time of data acquisition
Processing	Local Date and Time of data processing (time zone deduced using rover location)	UTC Date and Time of data processing

Coordinate Reference System

The project coordinate reference system is applied to all data imports and exports within the project. The selected project CRS is applied to imported survey control points, the post processed trajectory outputs, as well as the finalized LAS/LAZ and all corresponding data product outputs. Matching the project datum to the trajectory and survey control datum incurs the least amount of accuracy degradation.

Coordinate Reference System
Project Datum	The datum used to post process the project's output data products
Project datum epoch	The epoch used to post process the project's output data products
LAS output CRS	Horizontal and Vertical Coordinate Reference System of output LAS and other derived data products

Deliverable Products

This section presents a list of user selected output deliverable data products within Spatial Fuser Pipeline.

LiDAR

LiDAR
Output Files	Finalized LiDAR pointcloud data product file name
Format	Data product file format (LAS/LAZ)
Average Point Density	Average point density of finalized LiDAR pointcloud expressed in pulses/project unit^2
Specifications	Pointcloud classification and colorization details

Contours

Contours
Output File Name	Contour data product file name
Format	Data product file format (SHP)
Interval	User specified contour interval

DTM

Digital Terrain Model derived from ground classified LiDAR returns

DTM
Output File Name	DTM data product file name
Format	Data product file format (GeoTIFF)
Resolution	User specified pixel size

DSM

Digital Surface Model derived from highest hit LiDAR returns

DSM
Output File Name	DSM data product file name
Format	Data product file format (GeoTIFF)
Resolution	User specified pixel size

CHM

Canopy Height Model derived from the difference in elevation between highest hit LiDAR returns and ground classified LiDAR returns

CHM
Output File Name	CHM data product file name
Format	Data product file format (GeoTIFF)
Resolution	User specified pixel size

Decimated LiDAR DTM

Reduces the point density of LiDAR returns used to generate the Digital Terrain Model. The user specified value is used as the fixed/minimum point spacing between the output ground classified points

Decimated LiDAR DTM
Output File Name	Decimated LiDAR DTM data product file name
Format	Data product file format (LAS/LAZ)
Resolution	User specified point spacing

Acquisition

This section presents information pertaining to hardware used during data acquisition.

Hardware

Camera #
Model	Manufacturer and Model of camera used in project
Trigger Interval	Specifies whether system was triggered by time or interval during data acquisition, and the corresponding distance or time interval used for data acquisition

IMU
Type	Rover IMU model
Sample Rate	Rover IMU acquisition recording rate (Hz)

GNSS
Manufacturer	Rover GNSS antenna Manufacturer
Hardware Version	Rover GNSS antenna Hardware Version
Antenna	Rover GNSS antenna model

Platform

Platform
Survey Altitude (AGL)	The minimum, maximum, and average Above Ground Level (AGL) survey altitude. The distances are measured from LiDAR sensor to the ground profile within straight flightline intervals.
Approximate Survey Flight Speed	The minimum, maximum, and average speed of the platform carrying the payload. The velocities are measured during straight flightline intervals.

Reference Station # (L1 Antenna Phase Center) - Geographic 3d CRS (User Specified Datum)

Reference Station #	(L1 Antenna Phase Center) - Geographic 3d CRS (User Specified Datum)
Model	GNSS reference station antenna model
Latitude	Reference station geographic latitude in decimal degrees (user specified datum)
Longitude	Reference station geographic longitude in decimal degrees (user specified datum)
Ellipsoidal Height	Reference station L1 phase center ellipsoidal elevation (user specified datum)

Data Processing

Trajectory Post Processing

The trajectory data is processed using Phoenix LiDAR System's Navlab. Navlab is used to refine the system's position and attitude. A highly accurate post processed trajectory is generated from the coupled integration of GNSS and IMU data collected by the LiDAR System during the scanning mission.

Post Processed Trajectory
File	Filename of Post Processed Trajectory used for data product creation
Datum	Post processed trajectory datum
Epoch	Post processed Trajectory datum epoch

LiDAR Calibration

Trajectory Optimization

When the Trajectory Optimization tool is enabled, LiDARMill will perform feature matching using correspondences between overlapping swaths of LiDAR data to determine correction offsets that are applied to the mission’s trajectory. This will improve the resulting point cloud's relative accuracy.

Trajectory Optimization

ON/OFF

Fluctuating trajectory accuracy statistics from NavLab are used in conjunction with offsets in overlapping swaths of LiDAR to determine necessary trajectory optimizations along flightlines, in order to further refine the alignment of LiDAR swaths.

Scanner Calibration

When the Scanner Calibration tool is enabled, the LiDARMill applies an angular correction to the LiDAR sensor (pitch, yaw, roll correction) to resolve misalignments from IMU to sensor. Depending on the LiDAR model, an additional ranging scale correction, tilt angle offset, or encoder calibration correction may be calculated and applied.

Scanner Calibration

ON/OFF

Systematic attitude (roll, pitch, heading) misalignments between the system's IMU and LiDAR sensor are computed and minimized by comparing overlapping swaths of Lidar.

Image Rectification

The Calibrate Camera tool will calibrate the intrinsic and extrinsic camera parameters. Camera calibration requires correctly setting initial focal length.

Cam # Calibration

ON/OFF

The initial image positions and orientations are adjusted using an automated tie-point matching algorithm within LiDARMill. After alignment, an automated balancing procedure is used to minimize radiometric differences caused by illumination changes.

Accuracy

There are two ways to differentiate high accuracy survey control points - Ground Control Points (CONTROL) and Survey Checkpoints (CHECK). CONTROL are surveyed points used for data adjustments, and CHECK are surveyed points used for accuracy reporting. CONTROL points utilized for data adjustments should never be used to validate the accuracy of the data product.

CONTROL and CHECK survey points are generally collected at the same time, using the same methodology. Survey CHECK points are points with known coordinates that are used to validate the accuracy of the survey. CONTROL points leverage GNSS data to adjust survey models and improve their overall accuracy. Unlike CONTROL, CHECK points do not affect how the LiDAR survey is processed in any way.

LiDAR Relative Accuracy

Relative accuracy, the measure of how well overlapping flightlines match each other, is determined for the mission(s). Surface models are developed for each flightline. Relative accuracy is calculated from these surfaces using two metrics, magnitude and dZ. Magnitude is the average of the absolute values of the vertical offsets between a single flightline surface and points from overlapping flightlines. dZ is the average value of the vertical offsets between a single flightline surface and the points from overlapping flightlines. An average magnitude for all flightlines represents the project's overall relative accuracy.

Average Magnitude

LiDAR project's overall relative accuracy

Flightline	Magnitude	Dz
Flightline interval #	Average of the absolute values of the vertical offsets between a single flightline surface and points from overlapping flightlines	Average value of the vertical offsets between a single flightline surface and the points from overlapping flightlines

Vertical Adjustment (CONTROL)

LiDARMill determines vertical offsets between input CONTROL survey point elevations and ground classified point elevations within your point cloud. It then computes an average deviation magnitude, and vertically transforms the point cloud by the average magnitude, to best align the point cloud to the input CONTROL survey points. If there are no survey points labeled as "CONTROL", no vertical translation will be applied to trajectory/pointcloud.

Control Point Count

Number of "CONTROL" survey points used to compute LiDAR vertical translation

A single vertical offset is determined and applied in order to optimize the fit of LiDAR with existing ground control.

Trajectory	Translation
Post processed trajectory file name	Vertical translation applied to trajectory and resulting pointcloud (UP or DOWN), computed as average vertical offset between CONTROL survey points and LiDAR pointcloud

LiDAR Absolute Accuracy (CHECK)

Independent survey checkpoints are utilized to assess absolute accuracy of the LiDAR pointcloud. The absolute accuracy of LiDAR data is determined from measured vertical offsets between surveyed checkpoints and the LiDAR point cloud. A TIN (Triangulated Irregular Network) surface is created from LiDAR ground classified points, and used to measure the vertical offsets to CHECK points.

Note: Although CONTROL points and corresponding Dz offsets are included in the table below, only CHECK points are utilized for absolute accuracy calculation.

The table below presents statistical information computed from the elevation differences found in the "Survey Control Point Report - LiDAR" Table. If there are no survey points labeled as "CHECK", neither a statistical summary nor Dz histogram plot is computed.

Absolute Accuracy Determined Using "CHECK" Survey Control Points
Check Point Count	The number of CHECK survey points used for statistical analysis
RMSEz	The root mean square error (Z) of elevation differences
NVA at 95% Confidence Level	The non-Vegetated Vertical Accuracy at 95% Confidence Level = (RMSEz * 1.96)
Minimum Dz	The minimum value of elevation differences
Maximum Dz	The minimum value of elevation differences
Range	The range of elevation differences
Average Magnitude	The average of elevation differences

Survey Control Point Report - LiDAR

Table of elevation differences between the elevation of known survey CHECK points and the processed LiDAR pointcloud.

Type	ID	X	Y	Z	Laser Z	Dz
Type of Survey Control Point (CHECK or CONTROL)	Survey control point identifier	X/Easting coordinate of the survey control point	Y/Northing coordinate of the survey control point	Elevation coordinate of the survey control point	Elevation value derived from the LiDAR points at the survey control point's XY location	Difference between the survey control point elevation and the laser z elevation. If the value exceeds the outlier threshold, the value is displayed in red. If a CONTROL survey point is red, it was not used in determining vertical translation.

Dz Histogram

A plot displaying the histogram of the vertical distance error between surveyed CHECK point elevation values and the corresponding elevation value derived from the laser points at the survey CHECK point's XY location.

Maps

RGB

Pointcloud colored by corresponding RGB pixel values from mission imagery.

Intensity

Pointcloud colored by corresponding laser intensity.

Ellipsoidal Altitude

Pointcloud colored by corresponding ellipsoidal elevation values.

Height Above Ground

Pointcloud colored by distances above ground model derived from ground classified points

GCP Separation

Digital surface model with overlaid GCPs colored by dZ value.