Data Management Plan

Lidar-derived elevation data for the 2019 Oregon Lidar Consortium (OLC) West Metro 3DEP project area. The project area (PA) encompasses 486,551 acres. Data are within Multnomah County, Oregon. The nominal pulse density is eight pulses per square meter. Points that were determined to be geometrically invalid, or invalid surface returns, were removed from the data set. The hydro-flattened bare earth (BE) digital elevation model (DEM) raster grid cell size is 1 meter. The native projection is Albers Equal Area Conic, units are in meters. The native horizontal datum is North American Datum of 1983 (NAD83(2011)); the native vertical datum is North American Vertical Datum of 1988 (NAVD88); (Geoid 12B). Quantum Spatial Inc. collected the lidar and created this dataset in partnership with the Oregon Department of Geology and Mineral Industries (DOGAMI).

Data were subsequently reprocessed to Entwine Point Tile (EPT) format in web mercator projection with vertical meters. The EPT form of the data is used by the NOAA Digital Coast Data Access Viewer, which this metadata record is supporting. Additional processing steps may have been done by the Data Access Viewer and will be recorded in the lineage section.

Process Steps:

• 2019-12-10 00:00:00 - Lidar data acquisition occurred between May 8, 2019 and August 31, 2019. The survey utilized the Riegl 1560i laser systems mounted in a Cessna Caravan. Near nadir scan angles were used to increase penetration of vegetation to ground surfaces. Ground level GPS and aircraft IMU were collected during the flight. Processing.1. Airborne GPS and IMU data were merged to develop a Single Best Estimate (SBET) of the lidar system trajectory for each flight line. Flight lines and data were reviewed to ensure complete coverage of the study area and positional accuracy of the laser points. 2. Laser point return coordinates were computed using ALS Post Processor software and IPAS Pro GPS/INS software, based on independent data from the LiDAR system, IMU, and aircraft. 3. The raw LiDAR file was assembled into flight lines per return with each point having an associated x, y, and z coordinate. 4. Visual inspection of swath to swath laser point consistencies within the study area were used to perform manual refinements of system alignment. 5. Custom algorithms were designed to evaluate points between adjacent flight lines. Automated system alignment was computed based upon randomly selected swath to swath accuracy measurements that consider elevation, slope, and intensities. Specifically, refinement in the combination of system pitch, roll and yaw offset parameters optimize internal consistency. 6. Noise (e.g., pits and birds) was filtered using ALS postprocessing software, based on known elevation ranges and included the removal of any cycle slips. 7. Using TerraScan and Microstation, ground classifications utilized custom settings appropriate to the study area. 8. The corrected and filtered return points were compared to the RTK ground survey points collected to verify the vertical and horizontal accuracies. 9. Points were output as laser points, TINed and GRIDed surfaces.
• 2019-12-10 00:00:00 - Lidar Post-Processing: The calibrated and controlled lidar swaths were processed using automatic point classification routines in proprietary software. These routines operate against the entire collection (all swaths, all lifts), eliminating character differences between files. Proprietary software was used to thin this dataset from a pulse density of approximately 60 ppsm to the target 8 ppsm. The software randomly selects pulses to remove, including all returns associated, and keeps a user specified percentage of pulses to obtain desired point density. Data were then distributed as virtual tiles to experienced lidar analysts for localized automatic classification, manual editing, and peer-based QC checks. Supervisory QC monitoring of work in progress and completed editing ensured consistency of classification character and adherence to project requirements across the entire project. All classification tags were stored in the original swath files. After completion of classification and final QC approval, the NVA and VVA for the project were calculated. Sample areas for each land cover type present in the project were extracted and forwarded to the client, along with the results of the accuracy tests. Upon acceptance, the complete classified lidar swath files were delivered to the client. Points that were determined to be geometrically invalid, or invalid surface returns, were removed from the data set.
• 2019-12-10 00:00:00 - Hydro-Flattened Raster DEM Processing: Class 2 (Ground) LiDAR points in conjunction with the hydro-breaklines were used to create a 1-meter hydro-flattened raster DEM. Using automated scripting routines within LasTools, an GeoTIFF file was created for each tile. Each surface is reviewed using ArcMap to check for any surface anomalies or incorrect elevations found within the surface.
• 2024-01-31 00:00:00 - Data were converted to Entwine Point Tiles (EPT) in Web Mercator projection and units of meters by USGS. NOAA is leveraging the EPT files for use in the Digital Coast Data Access Viewer and created this metadata to support that usage. (Citation: Entwine Point Tiles)

Data is available online for bulk or custom downloads

Data is backed up to cloud storage.