2015 Puget Sound LiDAR Consortium (PSLC) LiDAR: WA DNR Lands (P1)

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This graphic shows the lidar coverage for the WA DNR P1 lands.

Date that the source FGDC record was last modified.

Converted from FGDC Content Standards for Digital Geospatial Metadata (version FGDC-STD-001-1998) using 'fgdc_to_inport_xml.pl' script. Contact Tyler Christensen (NOS) for details.

Partial upload of Positional Accuracy fields only.

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The LiDAR survey was accomplished using a Leica ALS70 and a Leica ALS80 system mounted in a Cessna Grand Caravan. Table 5 summarizes the settings used to yield an average pulse density of 8 pulses/m^2 over the WA DNR Lands project area; figure 5 shows acquisition flightlines. The Leica ALS70 and ALS80 systems can record unlimited measurements (returns) per pulse, but typically do not record more than five returns per pulse. It is not uncommon for some types of surfaces (e.g., dense vegetation or water) to return fewer pulses to the LiDAR sensor than the laser originally emitted. The discrepancy between first return and overall delivered density will vary depending on terrain, land cover, and the prevalence of water bodies. All discernible laser returns were processed for the output dataset.

1. Resolve kinematic corrections for aircraft position data using kinematic aircraft GPS and static ground GPS data. Develop a smoothed best estimate of trajectory (SBET) file that blends post-processed aircraft position with sensor head position and attitude recorded throughout the survey.

2. Calculate laser point position by associating SBET position to each laser point return time, scan angle, intensity, etc. Create raw laser point cloud data for the entire survey in *.las (ASPRS v. 1.2) format. Convert data to orthometric elevations by applying a geoid correction.

3. Import raw laser points into manageable blocks (less than 500 MB) to perform manual relative accuracy calibration and filter erroneous points. Classify ground points for individual flight lines.

4. Using ground classified points per each flight line, test the relative accuracy. Perform automated line-to-line calibrations for system attitude parameters (pitch, roll, heading), mirror flex (scale) and GPS/IMU drift. Calculate calibrations on ground classified points from paired flight lines and apply results to all points in a flight line. Use every flight line for relative accuracy calibration.

5. Classify resulting data to ground and other client designated ASPRS classifications (Table Assess statistical absolute accuracy via direct comparisons of ground classified points to ground control survey data.

6. Generate bare earth models as triangulated surfaces. Generate highest hit models as a surface expression of all classified points. Export all surface models as ESRI GRIDs in EDRAS Imagine (.img) format at a 1 meter pixel resolution.

7. Correct intensity values for variability and export intensity images as GeoTIFFs at a 0.5-meter pixel resolution.

The NOAA Office for Coastal Management (OCM) downloaded topographic files in .laz format from PSLC. The files contained lidar elevation, intensity, return number, class, scan angle and GPS time measurements. The data were received in Washington State Plane South Zone 4602, NAD83 coordinates and were vertically referenced to NAVD88 using the Geoid03 model. The vertical units of the data were feet. OCM performed the following processing for data storage and Digital Coast provisioning purposes:

1. The las files were converted from orthometric (NAVD88) heights to ellipsoidal heights using Geoid03, and from feet to meters.

2. The las files were converted from a Projected Coordinate System (WA SP South) to a Geographic Coordinate system (NAD83), converting from feet to decimal degrees.

3. Erroneous points were removed and class 11 points were reclassified to class 12 (overlap) to hold to the NOAA OCM classification scheme.

4. Filenames were altered with the addition of which WA DNR Land the tile resides. At the moment of publication of this metadata, P3 is not available publicly and therefore will not be available with this Digital Coast project.