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2009 Oregon Parks and Recreation Department Lidar: Columbia River

browse graphicThis kmz file shows the extent of coverage for the 2009 OPR Columbia River lidar data set.
The data set represents the lidar elevations along the Columbia River corridor in Oregon, including portions of the following counties: Gilliam, Hood River, Multnomah, Sherman, Umatilla, Wasco. The area includes portions of the Columbia River Gorge, as well as three smaller areas east of Hood River, OR. This data set covers 27,577 acres and was collected between December 7, 2009 and February 22, 2010. This data is part of a larger LiDAR survey effort by the US Army Corps of Engineers along the entire Columbia River. The lidar data are multiple return and are classified as unclassified and bare earth. The LiDAR survey used Leica ALS50 Phase II and ALS60 laser systems. The sensor scan angle was +/- 14 degrees from nadir with a pulse rate designed to yield an average native density (number of pulses emitted by the laser system) of > or = 8 points per square meter over terrestrial surfaces. In some areas of heavy vegetation or forest cover, there may be relatively few ground points in the LiDAR data. Elevation values for open water surfaces are not valid elevation values because few LiDAR points are returned from water surfaces. Watershed Sciences, Inc. collected the LiDAR and created this data set for Oregon Parks and Recreation Department.
Cite this dataset when used as a source.
Other Access Online access information not available.
Distribution Formats
  • LAZ
Distributor DOC/NOAA/NOS/OCM > Office for Coastal Management, National Ocean Service, National Oceanic and Atmospheric Administration, U.S. Department of Commerce
Dataset Point of Contact Brady Callahan
Oregon Parks and Recreation
Associated Resources
  • publication: 2011-11-01
Data Presentation Form: Digital image
Dataset Progress Status Complete
Data Update Frequency: Not planned
Purpose: Provide high resolution elevation data.
Use Limitations
  • These data depict the elevations at the time of the survey and are only accurate for that time. 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be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions.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. Any conclusions drawn from analysis of this information are not the responsibility of NOAA or any of its partners. These data are NOT to be used for navigational purposes.
  • While every effort has been made to ensure that these data are accurate and reliable within the limits of the current state of the art, NOAA cannot assume liability for any damages caused by any errors or omissions in the data, nor as a result of the failure of the data to function on a particular system. NOAA makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty.
  • DOC/NOAA/NOS/OCM > Office for Coastal Management, National Ocean Service, National Oceanic and Atmospheric Administration, U.S. Department of Commerce
  • Oregon Parks and Recreation Department
  • DOC/NOAA/NOS/OCM > Office for Coastal Management, National Ocean Service, National Oceanic and Atmospheric Administration, U.S. Department of Commerce
Time Period: 2009-12-07 to 2010-02-22
Spatial Reference System: urn:ogc:def:crs:EPSG::4269
Spatial Bounding Box Coordinates:
N: 45.919502
S: 45.516912
E: -119.134347
W: -122.336769
Spatial Coverage Map:
Theme keywords None
  • Bathymetry/Topography
  • LiDAR
  • Light Detection and Ranging
  • DEM
  • Digital Terrain Model
  • Oregon Parks and Recreation Department
  • Elevation data
  • Topography
  • Bare earth
  • High-resolution
  • Bare ground
  • DTM
Place keywords None
  • United States
  • Oregon
  • Pacific Northwest
  • Columbia River
  • Gilliam County
  • Hood River County
  • Multnomah County
  • Sherman County
  • Umatilla County
  • Wasco County
Use Constraints No constraint information available
Fees Fee information not available.
Lineage information for: dataset
  • DOC/NOAA/NOS/OCM > Office for Coastal Management, National Ocean Service, National Oceanic and Atmospheric Administration, U.S. Department of Commerce
  • DOC/NOAA/NESDIS/NGDC > National Geophysical Data Center, NESDIS, NOAA, U.S. Department of Commerce
Processing Steps
  • 2010-01-01T00:00:00 - Acquisition This LiDAR survey used Leica ALS50 Phase II and ALS60 laser systems. The sensor scan angle was +/- 14 degrees from nadir with a pulse rate designed to yield an average native density (number of pulses emitted by the laser system) of greater than or equal to 8 points per square meter over terrestrial surfaces. It is not uncommon for some types of surfaces (e.g. water) to return fewer pulses than the laser originally emitted. These discrepancies between 'native' and 'delivered' density will vary depending on the terrain, land cover, and the prevalence of water bodies. All areas were surveyed with an opposing flight line side-lap of greater than or equal to 60% (greater than or equal to 100% overlap) to reduce laser shadowing and increase surface laser painting. The Leica laser systems allow up to four range measurements (returns) per pulse, and all discernible laser returns were processed for the output data set. To accurately solve for laser point position (geographic coordinates x,y,z) the positional coordinates of the airborne sensor and the attitude of the aircraft were recorded continuously throughout the LiDAR data collection mission. Aircraft position 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 were indexed to GPS time.
  • 2010-01-01T00:00:00 - Processing 1. Laser point coordinates were computed using the IPAS and ALS Post Processor software suites based on independent data from the LiDAR system (pulse time, scan angle), and aircraft trajectory data (SBET). Laser point returns (first through fourth) were assigned an associated (x,y,z) coordinate along with unique intensity values (0-255). The data were output into large LAS v1.2 files; each point maintains the corresponding scan angle, return number (echo), intensity, and x,y,z (easting, northing, and elevation) information. 2. These initial laser point files were too large for subsequent processing. To facilitate laser point processing, bins (polygons) were created to divide the data set into manageable sizes (< 500 MB). Flightlines and LiDAR data were then reviewed to ensure complete coverage of the survey area and positional accuracy of the laser points. 3. Laser point data were imported into processing bins in TerraScan and manual calibration was performed to assess the system offsets for pitch, roll, heading, and scale (mirror flex). Using a geometric relationship developed by Watershed Sciences, each of these offsets were resolved and corrected if necessary. 4. LiDAR points were then filtered for noise, pits (artificial low points) and birds (true birds, as well as erroneously high points) by screening for absolute elevation limits, isolated points, and height above ground. Each bin was then manually inspected for remaining pits and birds and spurious points were removed. In a bin containing approximately 7.5 - 9.0 million points, an average of 50 - 100 points are typically found to be artificially low or high. Common sources of non-terrestrial returns are clouds, birds, vapor, haze, decks, brush piles, etc. 5. Internal calibration was refined using TerraMatch. Points from overlapping lines were tested for internal consistency and final adjustments were made for system misalignments (i.e., pitch, roll, heading offsets and scale). Automated sensor attitude and scale corrections yielded 3 - 5 cm improvements in the relative accuracy. Once system misalignments were corrected, vertical GPS drift was then resolved and removed per flight line, yielding a slight improvement (< 1 cm) in relative accuracy. 6. The TerraScan software suite is designed specifically for classifying near ground points (Soininen, 2004). The processing sequence began by removing all points that were not near the earth based on geometric constraints used to evaluate multi-return points. The resulting bare earth (ground) model was visually inspected and additional ground point modeling was performed in site-specific areas to improve ground detail. This manual editing of ground often occurs in areas with known ground modeling deficiencies such as: bedrock outcrops, cliffs, deeply incised stream banks, and dense vegetation. In some cases, automated ground point classification erroneously included known vegetation (i.e., understory, low/dense shrubs, etc.). These points were manually reclassified as non-grounds. Ground surface rasters were developed from triangulated irregular networks (TINs) of ground points.
  • 2011-10-01T00:00:00 - The NOAA Coastal Services Center (CSC) received the files in las format. The files contained lidar elevation and intensity measurements. The data was in Lambert Conformal Conic projection and NAVD88 Geoid 09 vertical datum. CSC performed the following processing for data storage and Digital Coast provisioning purposes: 1. The data were converted from Lambert Conformal Conic coordinates to geographic coordinates. 2. The data were converted from NAVD88 (orthometric) heights in international feet to GRS80 (ellipsoid) heights in meters using Geoid 09. 3. The data were filtered to remove outliers. 4. The LAS data were sorted by latitude and the headers were updated.
  • 2012-02-13T00:00:00 - The NOAA National Geophysical Data Center (NGDC) received lidar data files via ftp transfer from the NOAA Coastal Services Center. The data are currently being served via NOAA CSC Digital Coast at The data can be used to re-populate the system. The data are archived in LAS or LAZ format. The LAS format is an industry standard for LiDAR data developed by the American Society of Photogrammetry and Remote Sensing (ASPRS); LAZ is a loseless compressed version of LAS developed by Martin Isenburg ( The data are exclusively in geographic coordinates (either NAD83 or ITRF94). The data are referenced vertically to the ellipsoid (either GRS80 or ITRF94), allowing for the ability to apply the most up to date geoid model when transforming to orthometric heights.
Last Modified: 2013-06-04
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