Data Management Plan

In October 2013, WSI, a Quantum Spatial Company (QSI), was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR) data in the fall of 2013 for the Saddle Mountain site in south-central Washington. 172,093 acres collected.

Process Steps:

• 2014-03-01 00:00:00 - The LiDAR survey was accomplished with a Leica ALS60 system mounted in a Cessna Caravan, and a Leica ALS70 system mounted in a Partenavia aircraft, yielding an average pulse density of more than 8 pulses per sq. meter over the Saddle Mountain terrain. 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 native and delivered density will vary depending on terrain, land cover, and the prevalence of water bodies. The LiDAR data arrived to the office then QSI processing staff initiates a suite of automated and manual techniques to process the data into the requested deliverables. Processing tasks include GPS control computations, smoothed best estimate trajectory (SBET) calculations, kinematic corrections, calculation of laser point position, sensor and data calibration for optimal relative and absolute accuracy, and LiDAR point classification.
• 2014-03-01 00:00:00 - 1. Resolve kinematic corrections for aircraft position data using kinematic aircraft GPS and static ground GPS data. 2. 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. 3. 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 geoid03 correction. 4. 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 5. 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. 6. Classify resulting data to ground and other client designated ASPRS classifications. Assess statistical absolute accuracy via direct comparisons of ground classified points to ground control survey data. 7. Generate bare earth models as triangulated surfaces. Generate highest hit models as a surface expression of all classified points.
• 2014-08-20 00:00:00 - The NOAA Office for Coastal Management (OCM) downloaded topographic files in .txt format from PSLC's FTP site. The files contained lidar elevation, intensity, return number, class, scan angle and GPS time measurements. The data were received in Washington State Plane North Zone 4601, 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.

This data can be obtained on-line at the following URL:

https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=3675

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