2012 OLC Bathymetric Lidar: Sandy River (OR)

Area includes the Sandy River and a buffer of land around it.

Application to create custom data files by choosing data area, product type, map projection, file format, datum, etc. A new metadata will be produced to reflect your request using this record as a base.

Bulk download of data files in LAZ format, geographic coordinates, orthometric heights. Note that the vertical datum (hence elevations) of the files here are different than described in this document.

graphic showing the extent of the data set.

Planning:

The airborne survey was designed to collect a point density of 4-5 pulses/m2 for the topo-bathymetric LiDAR. The flight was planned with a scan angle of ±20o and 50% side-lap. The 50% side-lap was used to ensure uniform coverage and to minimize laser shadowing due to vegetation and terrain. The flights were conducted in the late fall during base flow conditions to maximize water clarity and ensure shallow depths (Figure 2).

The flight lines were developed using ALTM-NAV Planner (v.3.0) software and Leica Mission Pro Flight Planning and Evaluation (FPES) software. Efforts were taken to optimize flight paths by minimizing flight times while meeting all accuracy specifications. The WSI acquisition staff considered all factors such as air space restrictions, private property access, and GPS quality in the planning of this mission.

Lidar Survey:

Two lidar instruments were flown. A Riegel VQ-820-Q for bathymetric collection and a Lieca ALS60 for topographic collection.

The Riegl VQ-820-G uses a green-wavelength (μ = 532 nm) laser that, in addition to collecting vegetation and topography data, is able to penetrate the water surface with the 532-nm wavelength which provides for minimal spectral absorption. The sensor also collects both discrete returns (similar to the NIR data) and full-waveform data (every other pulse) for more rigorous feature extraction and evaluation of point returns. The recorded waveform enables range measurements for all discernible targets for a given pulse. The typical number of returns digitized from a single pulse ranged from 1 to 7 for the Sandy River project area.

The Leica ALS60 uses a NIR wavelength (μ =1,064nm) laser that has been proven to provide high value terrestrial topography data. The NIR wavelengths do not penetrate the water column and thus provide water surface returns for received pulses off of water surface. The Leica system collects 8-bit intensity information and does not store waveform information.

To accurately solve for laser point position (geographic coordinates x, y, and z), the positional coordinates of the airborne sensor and the attitude of the aircraft were recorded continuously throughout the LiDAR data collection mission. Position of the aircraft was measured twice per second (2 Hz) by an onboard differential GPS unit. Aircraft attitude was measured 200 times per second (200 Hz) as pitch, roll, and yaw (heading) from an onboard inertial measurement unit (IMU). To allow for post-processing correction and calibration, aircraft/sensor position and attitude data are indexed by GPS time.

Lidar Processing:

Prior to the mission, a boresight calibration flight was conducted in Corvallis, OR and processed by WSI to ensure accurate initial sensor alignment. An individual mission calibration was also performed on the Sandy River data set using Riegl’s RiProcess software. RiProcess was then used by WSI to further refine line-to-line calibration of the topo-bathymetric LiDAR dataset to match collected hard surface RTK control points.

Upon completion of calibration, Dewberry processed the LiDAR returns with a combination of manual and automated techniques using both the Riegl software and in-house proprietary software to differentiate the bathymetric and terrestrial data. WSI processed NIR LiDAR and the orthorectified digital imagery, which were also used to facilitate the processing of the bathymetric returns. Once bathymetric points were differentiated, they were spatially corrected for refraction through the water column based on the angle of incidence of the laser. Dewberry refracted water column points and classified the resulting point cloud. The resulting data was sent back to WSI for further review and product creation. Figure 4 shows the various datasets used in the bathymetric analysis while Table 7 summarizes the steps used to process the bathymetric LiDAR data.

Point Classification:

As with standard NIR LiDAR data, bathymetric (green) LiDAR returns are classified into categories according to whether the points are considered above ground, ground, or water. Additional LiDAR classifications were created for bathymetric processing by adding categories for channel bottom, water surface, and water column points.

Full Waveform Processing:

Initial echo analysis is accomplished with Riegl’s online waveform processing. In online waveform processing, discrete returns are digitized from the echo signal based on the amplitude and pulse deviation of returning energy. To facilitate discrimination of ground points versus water column points and bathymetry points, the Riegl VQ-820-G uses the online waveform processing system that generates a discrete point cloud dataset at time of capture (“online”) from the full waveform signal. The system also records geo-referenced waveforms for a subsample of the data (configured for every other pulse). The waveforms are used in determining accurate bathymetry in shallow submerged environments. The separation of the water surface and bottom return in shallow depths requires further analysis and customized methods to ‘decompose’ or ‘deconvolve’ the waveform.

Furthermore, certain parameters such as attenuation coefficients need to be set when processing data in various depth ranges and water column parameters. Information derived from the waveforms is used to set these parameters. The determination of the bottom return also needs to be corrected for the change in speed of light through the water column and the refraction of light at the air/water interface. The processed waveforms are used to validate the online digitization of the initial point cloud data.

The NOAA Office for Coastal Management received the lidar data from the Oregon Lidar Consortium. There were two sets of point clouds. One set contained only the points within the river boundaries, but included points classified as water surface and water column. The other set contained points from the full survey area, but only contained points classified as ground or unclassified. The second set of data was ingested into the Digital Coast Data Access Viewer.

Data were received in NAD83(CORS96) UTM zone 10 meters with vertical coordinates in NAVD88(GEOID09) meters. They were converted to geographic coordinates and ellipsoid heights for ingestion.

Metadata was not delivered with the data. This metadata was created from the WSI report.