2015 OLC Lidar: Wallowa, OR

The dataset encompasses 522 square miles in portions of Wallowa and Union Counties, Oregon. The highest hit digital surface models (DSM) represent the earth's surface with all vegetation and human-made structures included. The highest hit DSMs were derived from lidar data using TIN processing of the all-return point cloud. The bare earth digital elevation model (DEM) represents the earth's surface with all vegetation and human-made structures removed. The bare earth DEMs were derived from lidar data using TIN processing of the ground point returns. The DSM and DEM grid cell size is 3 feet. The projection is is Oregon Statewide Lambert Conformal Conic, units are in International Feet.The horizontal datum is NAD 83 (2011)and vertical datum is NAVD88 (Geoid 12A). Some elevation values have been interpolated across areas in the models where there is no elevation data (e.g. over water, over dense vegetation). Watershed Sciences, Inc. collected the lidar and created this data set for the Oregon Department of Geology and Mineral Industries (DOGAMI).

This dataset provides high resolution terrain elevation and land cover elevation data in the OLC Walllowa project area.

xyz location information for objects in the area

This dataset was contracted by Oregon Department of Geology and Mineral Industries (DOGAMI). Information regarding the use of this dataset should be directed to the owner.

Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office for Coastal Management or its partners

Data is available online for custom downloads

None

Users should be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its limitations.

Vertical accuracy analysis of delivered lidar data consisted of differencing collected GCP data and the lidar Digital Elevation Models (DEM) to expose offsets. These offsets were used to produce a mean vertical error and vertical RMSE value for the entire delivered data set. Project specifications list the maximum acceptable mean vertical offset to be 0.20 meters (0.65 feet) and the maximum vertical RSME to not exceed 0.093 meters (0.30 feet).

A total of 258 measured GCPs were obtained in the OLC Wallowa 2015 LIDAR Project area and were compared with the lidar elevation grids. The data delivered to DOGAMI was found to have a mean vertical offset of -0.02 meters (-0.05 feet) and an RMSE value of 0.06 meters (0.19 feet). Offset values ranged from -0.18 meters (-0.61 feet) to 0.19 meters (0.62 feet).

Consistency refers to lidar elevation differences between overlapping flight lines. Consistency errors are created by poor lidar system calibration settings associated with sensor platform mounting. Errors in consistency manifest as vertical offsets between individual flight lines. Lidar flight lines have been examined to ensure that there was at least 60% sidelap, there are no gaps between flightlines, and the vertical offsets between flight line must be less than 0.15m (0.49 feet).

To quantify the magnitude of this error, 4550 of 4558 delivered data tiles (99.8%) were examined for vertical offset between flight lines. Data tiles with less than 1000 points were not used in analysis. Each tile measured 750 x 750 meters in size. The average number of points used for flight line comparison was 20,251,265.29 points per tile. Error measurements were calculated by differencing the nearest point from an adjacent flight line within 1 meter in the horizontal plane and 0.2 meters in the vertical plane. Each flight line was compared to adjacent flight lines, and the average magnitude of vertical error was calculated. 328 flight lines out of 344 total flight lines (95.3%) were sampled and compared for consistency.

Results of the consistency analysis found the average flight line offset to be 0.04 meters (0.13 feet) with a maximum error of 0.07 meters (0.24 feet). Distribution of error showed 91.2% of all error was less than 0.05 meters (0.25 feet) and 96.6% less than 0.06 meters (0.19 feet). These results show that all data are within specification.

DOGAMI has specified that the aggregate design multi-swath pulse density for the Wallowa project must be 8.0 pulses per square meter or higher. Pulse density is calculated as the number of pulses per unit area, commonly measured as pulses per square meter. This calculation is based on the number of first return pulses divided by the area of the tile.

To quantify pulse density of the OLC Wallowa 2015 Lidar Project, 1246 all-return LAS files (100%) were parsed into first-return point files and compared to their data extents. Results of the pulse density analysis found the average pulse density to be 9.25 pulses per m². Certain types of surfaces (dense vegetation, water) may return fewer pulses than the laser originally emitted; therefore density values can vary according to terrain and land cover. Pulse densities for OLC Wallowa 2015 Lidar Project LAS tiles ranged from 0.38 pulses per m^2; to 23.5 pulses per m^2;. 946 LAS files out of 1246 (76%) have a pulse density of 8.00 pulses per m^2;. These results show that all data are within tolerances of pulse density according to the contract agreement.

The approach adopted for DOGAMI lidar surveys was comprised of three components:

1) Verify the horizontal and vertical coordinates established by Watershed Sciences for a select number of survey monuments used to calibrate the lidar survey. These surveys typically involved a minimum of two hours of GPS occupation over a known point. The collected data were then submitted to the National Geodetic Survey (NGS) Online Positioning User Service (OPUS) for post-processing against several Continuously Operating Reference Stations (CORS) operated by the NGS.

2) Collect GCPs along relatively flat surfaces (roads, paths, parking lots etc.). This step involved the collection of both continuous measurements (from a vehicle as well as from a backpack) as well as static measurements (typically 5 epochs).

3) Having collected the GCP data, the GPS data was post-processed using Trimble Business Center software. Data post-processing typically involved calibrations against at least three CORS stations as well as from local site calibrations performed in the field using those benchmarks that had been independently verified. Data is post processed to refine measurements so that horizontal and vertical errors are less than 0.02 meters (0.065 feet). Horizontal accuracy of data is tested by reoccupying a sample subset of survey monuments used for processing of lidar data. Each occupation's x and y coordinates are compared with the vendor coordinates for offsets.

Data is backed up to tape and to cloud storage.

Watershed Sciences Inc. has collected Light Detection and Ranging (LIDAR) data in the Milton-Freewater Study Area for the Oregon Department of Geology and Mineral Industries (DOGAMI).

NOAA OCM has taken the data and ingested it into the Digital Coast Data Access Viewer for distribution.