2019 DAS - GEO Lidar: Gilchrist, OR

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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.

The Data Access Viewer (DAV) allows a user to search for and download elevation, imagery, and land cover data for the coastal U.S. and its territories. The data, hosted by the NOAA Office for Coastal Management, can be customized and requested for free download through a checkout interface. An email provides a link to the customized data, while the original data set is available through a link within the viewer.

This graphic displays the footprint for this lidar data set.

Link to project report for this data set.

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.

Data collector's website

Ground Survey

QSI conducted a ground survey to support airborne LiDAR collection between June 7 and June 12, 2019.

Monumentation

A combination of QSI-set monuments, NGS monuments, and permanent base stations from the Oregon Real-time GNSS Network (ORGN) were used for collection of ground survey points (GSPs) using real time kinematic (RTK) and post processed kinematic (PPK) survey techniques. Monument locations were selected with consideration for satellite visibility, field crew safety, and optimal location for GSP coverage. RINEX files and final coordinates for flight support were provided using the ORGN. The coordinates used for these stations are provided as Antenna Reference Point (ARP) height in NAD83(2011) epoch 2010.00. Please see page 6 for ORGN locations and QSI and NGS monument locations in tabular and cartographic format.

Ground Survey Points

The ground survey for the DAS-GEO Gilchrist LiDAR project was conducted between June 7 and June 12, 2019. Ground survey data were used for data calibration and accuracy assessment purposes. Ground survey points (GSPs) were collected using RTK techniques. For RTK surveys, either the ORGN was utilized to broadcast a kinematic correction to a roving receiver; or a base receiver was positioned at a nearby monument to broadcast a kinematic correction to a roving receiver. For PPK surveys, however, these corrections were post-processed. RTK and PPK surveys recorded observations for a minimum of five seconds on each GCP/GSP in order to support longer baselines for post-processing. All GSP measurements were made during periods with a Position Dilution of Precision (PDOP) no greater than 3.0 and in view of at least six satellites for both receivers. Relative errors for the position were required to be less than 1.5 centimeters horizontal and 2.0 centimeters vertical in order to be accepted.

Airborne Survey

All data for the 2019 DAS-GEO Gilchrist project area were flown between June 1 and June 5, 2019 utilizing a Leica ALS80 sensor mounted in a Cessna Grand Caravan aircraft. The LiDAR system for the Leica ALS80 sensor was set to acquire ≥333,000 laser pulses per second (i.e. 333 kHz pulse rate) and flown at 1,650 meters above ground level (AGL), capturing a 40 degree field of view. These settings and flight parameters are developed to yield points with an average native density of ≥8 over terrestrial surfaces. The native pulse density is the number of pulses emitted by the LiDAR system. Some types of surfaces (e.g., 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. The study area was surveyed with opposing flight line side-lap of ≥60% (≥100% overlap) for the ALS80 sensor to reduce laser shadowing and increase surface laser painting. The system allows for an unlimited number of LiDAR return measurements per pulse, and all discernible laser returns were processed for the output data set. The LiDAR sensor operators constantly monitored the data collection settings during acquisition of the data, including pulse rate, power setting, scan rate, gain, field of view, and pulse mode. For each flight the crew performed airborne calibration maneuvers designed to improve the calibration results during the data processing stage. The LiDAR coverage was completed with no data gaps or voids, barring non-reflective surfaces (e.g., open water, wet asphalt). All necessary measures were taken to acquire data under conditions (e.g., minimum cloud decks) and in a manner (e.g., adherence to flight plans) that prevented the possibility of data gaps. All QSI LiDAR systems are calibrated per the manufacturer and our own specifications, and tested by QSI for internal consistency among every mission using proprietary methods.

To solve for laser point position, an accurate description of aircraft position and attitude is vital. Aircraft position is described as x, y, and z and was measured twice per second (two hertz) by an onboard differential GPS unit. Aircraft attitude is described as pitch, roll, and yaw (heading) and was measured 200 times per second (200 hertz) from an onboard inertial measurement unit (IMU).

Weather conditions were constantly assessed in flight, as adverse conditions not only affect data quality, but can prove unsafe for flying.

Processing

Once the LiDAR data arrived in the laboratory, QSI employed a suite of automated and manual techniques for processing tasks. Processing tasks included: GPS, kinematic corrections, calculation of laser point position, relative accuracy testing, classification of ground and non-ground points, and assessments of statistical absolute accuracy. The general workflow for calibration of the LiDAR data was as follows:

Resolve GPS kinematic corrections for aircraft position data using kinematic aircraft GPS (collected at two hertz) and static ground GPS (one hertz) data collected over geodetic controls.

Develop a smoothed best estimate of trajectory (SBET) file that blends post-processed aircraft position with attitude data. Sensor heading, position, and attitude are calculated throughout the survey.

Calculate laser point position by associating SBET information to each laser point return time, with offsets relative to scan angle, intensity, etc. included. This process creates the raw laser point cloud data for the entire survey in *.las (ASPRS v. 1.4) format, in which each point maintains the corresponding scan angle, return number (echo), intensity, and x, y, z information. These data are converted to orthometric elevation (NAVD88) by applying a Geoid 12B correction.

Import raw laser points into subset bins (less than 500 megabytes, to accommodate file size constraints in processing software). Filter for noise and perform manual relative accuracy calibration.

Classify ground points and test relative accuracy using ground classified points per each flight line.

Perform automated line-to-line calibrations for system attitude parameters (pitch, roll, heading), mirror flex (scale), and GPS/IMU drift. Calibrations are performed on ground classified points from paired flight lines. Every flight line is used for relative accuracy calibration.

Assess non-vegetated vertical accuracy via direct comparisons of ground classified points to reserved ground survey data.

Assign headers (e.g., projection information, variable length record, project name, GEOTIFF tags) to *.las files.

The NOAA Office for Coastal Management (OCM) received 662 lidar point cloud files in laz format from the Oregon Parks and Recreation Dept. The files contained lidar elevation and intensity measurements. The data were in Oregon Lambert Conformal Conic (NAD83 2011), international feet coordinates and NAVD88 (Geoid12B) elevations in feet. The data were classified as: 1-Unclassified, 2-Ground, 7 - Low Noise, 17 - Bridge Decks, 18 - High Noise. OCM processed all classifications of points to the Digital Coast Data Access Viewer (DAV). Classes available on the DAV are: 1, 2, 7, 17, 18. No metadata record was provided for this data set. This record was created by the NOAA Office for Coastal Management (OCM) using information from the data report.

OCM performed the following processing on the data for Digital Coast storage and provisioning purposes:

1. An internal OCM script was run to check the number of points by classification and by flight ID and the gps and intensity ranges.

2. Internal OCM scripts were run on the laz files to convert from orthometric (NAVD88) elevations to ellipsoid elevations using the Geoid 12B model, to convert from Oregon Lambert Conformal Conic (NAD83 2011), international feet coordinates to geographic coordinates, to convert vertical elevations from feet to meters, to assign the geokeys, to sort the data by gps time, and zip the data to database and to http.