2017 USDA Forest Service Lidar: Olympic National Forest, WA

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Bulk download of data files in LAZ format, geographic coordinates, orthometric heights. Note that the vertical datum (hence elevations) of the files here are different than described in this document. They will be in an orthometric datum.

Link to the Tetra Tech Technical Lidar Report from the Washington Lidar Portal.

The Data Access Viewer (DAV) allows a user to search for and download elevation, imagery, and land cover data for the coastal U.S. and its territories. The data, hosted by the NOAA Office for Coastal Management, can be customized and requested for free download through a checkout interface. An email provides a link to the customized data, while the original data set is available through a link within the viewer.

Lidar Acquisition

The LiDAR acquisition took place during 4 flight missions on October 29, 2017 and December 11, 2017, December 13 - 14, 2017. Weather conditions during collection were clear and free of cloud/fog, precipitation, and any other weather phenomena which would negatively impact the collection. Collection occurred during leaf-off conditions and with no snow in the area of interest, as to acquire the most accurate ground model possible. 105 flight lines of LiDAR were collected to achieve the required specifications for each area. The LiDAR data was collected using an Riegl LMS-Q1560 and Optech Galaxy T1000 system. For the Q1560 LiDAR acquisition, the nominal flying height was 1400m above ground level (AGL) and flying speed was approximately 145kts. The Galaxy LiDAR acquisition was flown from 975m AGL at a similar flying speed. The scan field of view for the Riegl Q1560 is 29 degrees either side of nadir, for a total scan field of view (FoV) of 58 degrees and scans at a rate of 800 kHz. Due to the nature of the 4-sided rotating mirror in Riegl scanners, only 2/3 pf pulses are recorded (533 kHz usable). The Galaxy acquires a variable FoV (10 - 60 degrees) in order to account for terrain variation, and was operated at a 400 kHz scan rate.

The settings on the sensors yield an average pulse density of 4+ pulses per flight line. Acquiring data with double coverage ensures that the desired point density is met. Note that each pulse may result in one or more returned points as the pulse filters through vegetation, etc. Water or highly absorbent

material may result in very few or no LiDAR returns as these materials poorly reflect the laser pulse. During the flight, the airborne trajectory was monitored with kinematic AGPS combined with IMU observations. The LiDAR data was combined with the GPS/IMU data to create the raw .las files. These raw files were then calibrated to create a dataset that was then used to create the desired mapping products.

GNSS post-processing determines the position and attitude of the aircraft at 200Hz along the entire flight path. This data is logged for the Riegl Q1560 via an Applanix POS AV510 and an Applanix AP60 for the Optech Galaxy. Post-processing requires data from the onboard GNSS and Inertial Measurement

Unit (IMU) as well as data from one or more static GNSS base station(s) with known coordinates. Post processing is performed in Applanix PosPAC MMS software. Here the aircraft GNSS / IMU data is referenced to the base station data to provide adjusted positions for the aircraft in latitude, longitude,

and height, roll, pitch, and yaw / heading. The final trajectory is then smoothed, and exported in .pos format for use in the LiDAR point cloud extraction. The resulting flight path is commonly referred to as a Smoothed Best Estimate of Trajectory (SBET). In this project location there is a great distribution of 1Hz CORS and WSRN reference stations publicly available. These base stations were combined into an Applanix Smart Base during post-processing to

model GNSS corrections over the entire AOI. The result is a high accuracy baseline with reduced dropouts or PDOP spikes due to satellite loss on a single station. Mission planning ensures the project is flown during periods of good satellite visibility, resulting here in an average PDOP of 1.5 and maximum spike to 2.8.

Lidar Boresight

Prior to acquisition of the project area, a boresight mission was flown over Port Coquitlam, BC in an area with many buildings and other planar objects. The boresight flight consisted of 3 lines in a north-south direction and 3 lines in an east-west direction, with significant overlap between all lines. The boresight data was then calibrated using Riegl's RiProcess software. A quality check was performed using matching tie planes which are calculated automatically and analyzed via a least-squares adjustment. Adjustments to the scanner orientation parameters can then be calculated to minimize residuals between the tie planes. Manual cross section checks were also performed to verify the automatic results. Once deemed properly calibrated, scanner parameters are then carried forward with all subsequent acquisition datasets for the project.

Data Calibration

The Q1560 LiDAR data was processed through RiProcess in a similar process as with the Boresight. The LAS data is then exported each scan line. All data was projected into the OR_WA Albers projection and adjusted to the proper geoid (GEOID12B) at this time. After export, the Q1560 dataset was combined with the Optech data. The project was then examined for relative and absolute accuracy within each flight and mission‐to‐mission. Control points measured by CompassData Inc. were provided to Eagle Mapping to aid with quality assessment. Flight lines which overlapped these control points were then examined in detail to identify systematic positioning errors which could be compensated for with further processing. A slight vertical bias was identified in the datasets acquired by both scanners, so these datasets were shifted vertically to better fit the ground control points. Q1560 data was shifted by ‐0.106m and Galaxy L1000 data was shifted by +0.259m. These offsets can be attributed to biases in the system boresight and/or lever arm values, and are easily corrected for.

Once the QA of the collected LiDAR was complete, classification of the LiDAR began. An automated ground classification filter was developed using TerraScan software, and applied to the LiDAR data. After the automated filter was run, a manual QC was conducted to review of all of LiDAR within the area of interest. Special attention was used in both the automation and manual classification to ensure that the ground was classified correctly due to the density of the low vegetation. The LiDAR was classified

into:

1 - Unclassified

2 - Ground

7 - Low Point

18 - High Noise

Once the review of the classified LiDAR was complete, DTMs and DSMs were created. The DTMs were created using the ground classified LiDAR. The DSMs were created using first and only return LiDAR points. In addition, intensity Images were generated from the LiDAR dataset.

The NOAA Office for Coastal Management (OCM) was provided this data set from the office of the Washington Lidar Portal. The total number of files received and processed was 336.

The data were in Washington State Plane South (NAD83 2011), US survey feet coordinates and NAVD88 (Geoid12A) elevations in feet. The data were classified as: 1 - Unclassified, 2 - Ground, 7 - Low Noise, 18 - High Noise. OCM processed all classifications of points to the Digital Coast Data Access Viewer (DAV). Classes available in the DAV are: 1, 2, 7, 18.

OCM performed the following processing on the data for Digital Coast storage and provisioning purposes:

1. An internal OCM script was run to check the number of points by classification and by flight ID and the gps and intensity ranges.

2. Internal OCM scripts were run on the laz files to convert from orthometric (NAVD88) elevations to ellipsoid elevations using the Geoid12A model, to convert to geographic coordinates, to convert from elevations in feet to meters, to assign the geokeys, to sort the data by gps time and zip the data to database and to the Amazon S3 bucket.