2009 - 2011 OLC Lidar: Deschutes, OR

Create custom data files by choosing data area, product type, map projection, file format, datum, etc.

Simple download of data files.

This graphic shows the lidar coverage for the 2009 - 2011 topographic lidar acquisition in the Deschutes study area.

Link to the lidar report.

Link to the Acceptance Report.

Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud.

Link to view the point cloud, using the Entwine Point Tile (EPT) format, in the 3D Potree viewer.

Link to custom download, from the Data Access Viewer (DAV), the raster Digital Elevation Model (DEM) data that were created from this lidar data set.

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.

Partial upload to move data access links to Distribution Info.

Watershed Sciences, Inc. has collected Light Detection and Ranging (LiDAR) data of the Deschutes Study Area for the Oregon Department of Geology and Mineral Industries (DOGAMI). The area of interest (AOI) totals 3,001 square miles (1,920,429 acres) and the total area flown (TAF) covers 3,053 square miles (1,953,949 acres). The TAF acreage is greater than the original AOI acreage due to buffering and flight planning optimization (Figure 1.1 below). DOGAMI data are delivered in OGIC (HARN): Projection: Oregon Statewide Lambert Conformal Conic; horizontal and vertical datum: NAD83 (HARN)/NAVD88 (Geoid03); units: International Feet.

The LiDAR survey utilized Leica ALS50 Phase II and ALS60 sensors mounted in multiple Cessna Caravan 208Bs. The Leica systems were set to acquire greater than or equal to 105,000 laser pulses per second (i.e. 105 kHz pulse rate) and flown at 900 and 1300 meters above ground level (AGL), capturing a scan angle of plus or minus 14 degrees from nadir. These settings are developed to yield points with an average native density of 8 points per square meter over terrestrial surfaces. The native pulse density is the number of pulses emitted by the LiDAR system. Some types of surfaces (i.e. dense vegetation or water) may return fewer pulses than the laser originally emitted. Therefore, the delivered density can be less than the native density and vary according to distributions of terrain, land cover and water bodies.

Processing.

1. 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.

The NOAA Office for Coastal Management (OCM) received the data in laz format from DOGAMI. The files contained lidar elevation and intensity measurements. The data were in Oregon Statewide Lambert (NAD83 HARN) International feet coordinates and NAVD88 (Geoid03) elevations in International feet. OCM did the following processing to the data for Digital Coast storage and provisioning purposes:

1. Converted from Oregon Statewide Lambert (NAD83 HARN) International feet coordinates to geographic coordinates

2. Converted from NAVD88 elevations to NAD83(2011) ellipsoid elevations using Geoid03 grids

3. Converted the vertical units from International feet to meters

4. Copied the laz files to database and https