Data Management Plan (Deprecated)

Product: These lidar data are processed Classified LAS 1.4 files, formatted to 9,946 individual 3000 ft x 3000 ft tiles; used to create intensity images, 3D breaklines and hydro-flattened DEMs as necessary.

Geographic Extent: The project area encompasses 2,054,958.7 acres and is located in Baker, Grant, Harney, Morrow, Umatilla, Union, and Wheeler County, Oregon.

Dataset Description of Original Data: 2020 OLC Upper John Day 3DEP project called for the planning, acquisition, processing and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meter. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 1.3. The data was developed based on the Lambert Conic Conformal projection, units are in International feet. 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). Lidar data was delivered as as processed Classified LAS 1.4 files, formatted to 9,946 individual 3000 ft x 3000 ft tiles, as tiled Intensity Imagery, and as tiled bare earth and highest hit DEMs; all tiled to the same 3000 ft x 3000 ft schema. Points that were determined to be geometrically invalid, or invalid surface returns, were removed from the data set.

Ground Conditions: 2020 LiDAR data were acquired between November 15, 2019 and August 20, 2020, while no snow was on the ground and rivers were at or below normal levels.

This metadata record supports the data entry in the NOAA Digital Coast Data Access Viewer (DAV). For this data set, the DAV is leveraging the Entwine Point Tiles (EPT) hosted by USGS on Amazon Web Services.

Lineage Statement:
The NOAA Office for Coastal Management (OCM) ingested references to the USGS Entwine Point Tiles (EPT) hosted on Amazon Web Services (AWS) into the Digital Coast Data Access Viewer (DAV). The DAV accesses the point cloud as it resides on AWS under the usgs-lidar-public-container.

Process Steps:

• 2021-05-13 00:00:00 - Lidar data acquisition occurred between November 15, 2019 and August 20, 2020. The 2020 survey utilized the Riegl 1560ii laser systems mounted in a Cessna 208B. 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.
• 2020-08-21 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. 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 for the project were calculated.
• 2020-08-21 00:00:00 - Raster DEM Processing: Class 2 (Ground) LiDAR points were used to create a 3-foot 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.
• Original point clouds in LAS/LAZ format were restructured as Entwine Point Tiles and stored on Amazon Web Services. The data were re-projected horizontally to WGS84 web mercator (EPSG 3857) and the vertical units were converted to meters (NAVD88 Geoid12B).
• 2024-06-26 00:00:00 - The NOAA Office for Coastal Management (OCM) created references to the Entwine Point Tiles (EPT) that were ingested into the NOAA Digital Coast Data Access Viewer (DAV). No changes were made to the data. The DAV will access the point cloud as it resides on Amazon Web Services (AWS) under the usgs-lidar-public container. This is the AWS URL being accessed: https://s3-us-west-2.amazonaws.com/usgs-lidar-public/OR_UpperJohnDay_1_2020/ept.json

Data is available online for bulk and custom downloads.

Data is backed up to cloud storage.