2016 OLC Lidar: Milton Freewater, OR

Milton Freewater, OR

Collection time for the lidar.

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 point cloud data files in LAZ format, geographic coordinates, orthometric heights.

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.

Report by DOGAMI describing data quality tests and results.

Report by Watershed Sciences Inc detailing the project and processes.

Acquisition.

LiDAR data acquisition was conducted from June 06 to June 20, 2016. The survey utilized a Leica ALS 80 laser system mounted in a Cessna 208. Scan angles near nadir were used to increase penetration of vegetation to ground surfaces. Ground level GPS and aircraft IMU were collected during the flight.

Processing.

1. TRAJECTORY: Aircraft trajectory (position and attitude) were calculated based on on-board GPS and IMU data with post-processing refinement through coincident static GPS collection.

2. POST-PROCESSING: Laser point return coordinates (x,y,z) were computed using sensor-specific post processing software, combining LiDAR return range and intensity information with aircraft trajectory information.

3. INITIAL QAQC: The post-processed LiDAR files were assembled into flight lines and reviewed for gaps and consistency, as well as systematic noise.

4. CALIBRATION: Custom algorithms evaluated individual swaths for misalignments based on IMU configuration as well as aircraft attitude variability. Offsets were resolved through surface and linear matching algorithms that minimize variability in elevation and slope. Descriptive statistics, thresholds, and specifications providing transparency for data calibration are discussed in the accompanying Data Report.

5. GROUND MODELING: Ground classified point cloud was generated through proprietary data processing tools, with settings and thresholds appropriate to landscape and vegetation condition.

6. ARTIFACT FILTRATION: Noise and processing artifacts were filtered using post-processing software and proprietary quality control methods.

7. ACCURACY ASSESSMENT: Vertical accuracy for the LiDAR dataset was assessed against Ground Check Points (GCP) distributed throughout the study area. See the accompanying Data Report for methodology, descriptive statistics, and relevant standards and reporting language.

NOAA/OCM received the data from DOGAMI in Arc Grid format . Data were in NAD83(2011) Oregon Lambert horizontally and NAVD88 (Geoid12a) vertically. All units were international feet. For ingest into the Digital Coast Data Access Viewer the data was converted to NAD83(2011) geographic coordinates and the vertical datum was changed to NAD83(2011) ellipsoid heights in meters using GEOID12a.