• Sherri L. Johnson - Principal Investigator
  US Forest Service ;Pacific NW Research Station ;3200 SW Jefferson Way, Corvallis, OR, 97331, USA
  Phone: 541-758-7771
  Email: sherri.johnson2@usda.gov, sherri.johnson@oregonstate.edu
  URL: https://www.fs.fed.us/research/people/profile.php?alias=sherrijohnson
• Julia A. Jones - Principal Investigator
  Oregon State University;Department of Geosciences; Wilkinson Hall 104, Corvallis, OR, 97331-5506, USA
  Phone: (541) 737-1224
  Email: Julia.Jones@oregonstate.edu, geojulia@comcast.net
  URL: http://ceoas.oregonstate.edu/profile/jones/
  ORCID: http://orcid.org/0000-0001-9429-8925
• Matthew G Betts - Principal Investigator
  Department of Forest Ecosystems and Society; 201E Richardson Hall; College of Forestry; Oregon State University, Corvallis, OR, 97331
  Phone: (541) 737-3841
  Email: matt.betts@oregonstate.edu
  URL: http://www.fsl.orst.edu/flel/index.htm
• Michael P. Nelson - Principal Investigator
  Department of Forest Ecosystems and Society; 201K Richarson Hall; College of Forestry; Oregon State University, Corvallis, OR, 97331
  Phone: 541-737-9221
  Email: mpnelson@oregonstate.edu
  URL: http://www.michaelpnelson.com
  ORCID: http://orcid.org/0000-0001-6917-4752
• David Bell - Principal Investigator
  Email: david.bell@usda.gov, david.bell@oregonstate.edu
  URL: https://lemma.forestry.oregonstate.edu/about/david-bell

• The H.J. Andrews Experimental Forest is a living laboratory that provides unparalleled opportunities for the study of forest and stream ecosystems in the central Cascade Range of Oregon. Since 1980, as a part of the National Science Foundation Long Term Ecological Research (NSF-LTER) program, the Andrews Experimental Forest has become a leader in the analysis of forest and stream ecosystem dynamics.
• Long-term field experiments and measurement programs have focused on climate dynamics, streamflow, water quality, and vegetation succession. Currently researchers are working to develop concepts and tools needed to predict effects of natural disturbance, land use, and climate change on ecosystem structure, function, and species composition.
• The Andrews Experimental Forest is administered cooperatively by the USDA Forest Service Pacific Northwest Research Station, Oregon State University and the Willamette National Forest. Funding for the research program comes from the National Science Foundation (NSF), US Forest Service Pacific Northwest Research Station, Oregon State University, and other sources.

Data were provided by the HJ Andrews Experimental Forest research program, funded by the National Science Foundation's Long-Term Ecological Research Program (DEB 2025755), US Forest Service Pacific Northwest Research Station, and Oregon State University. National Science Foundation: DEB1440409

• Long-Term Ecological Research
  The Andrews Forest is situated in the western Cascade Range of Oregon, and covers the entire 15,800-acre (6400-ha) drainage basin of Lookout Creek. Elevation ranges from 1350 to 5340 feet (410 to 1630 m). Broadly representative of the rugged mountainous landscape of the Pacific Northwest, the Andrews Forest contains excellent examples of the region's conifer forests and associated wildlife and stream ecosystems. These forests are among the tallest and most productive in the world, with tree heights of often greater than 250 ft (75 m). Streams are steep, cold and clean, providing habitat for numerous aquatic organisms.

• The LiDAR survey utilized a Leica ALS60 Phase II sensor in a Cessna Caravan 208B. The sensors operate with Automatic Gain Control (AGC) for intensity correction. The Leica systems were set to acquire 105,000 laser pulses per second (i.e. 105 kHz pulse rate) and flown at 900 meters above ground level (AGL), capturing a scan angle of ±14o from nadir. These settings were developed to yield points with an average native pulse density of 8 pulses per square meter over terrestrial surfaces. It is not uncommon for some types of surfaces (e.g. dense vegetation or water) to return fewer pulses than the laser originally emitted. These discrepancies between ‘native’ and ‘delivered’ density will vary depending on terrain, land cover, and the prevalence of water bodies.
• All areas were surveyed with an opposing flight line side-lap of =50% (=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 dataset. 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 are indexed by GPS time.
• See the complete documentation for more detail descriptions of the methodology.

• 1. Resolved kinematic corrections for aircraft position data using kinematic aircraft GPS and static ground GPS data. Software: Waypoint GPS v.8.10, Trimble Geomatics Office v.1.62
• 2. Developed a smoothed best estimate of trajectory (SBET) file that blends post-processed aircraft position with attitude data. Sensor head position and attitude were calculated throughout the survey. The SBET data were used extensively for laser point processing. Software: IPAS v.1.35
• 3. Calculated laser point position by associating SBET position to each laser point return time, scan angle, intensity, etc. Created raw laser point cloud data for the entire survey in *.las (ASPRS v. 1.2) format. Software: ALS Post Processing Software v.2.70
• 4. Imported raw laser points into manageable blocks (less than 500 MB) to perform manual relative accuracy calibration and filter for pits/birds. Ground points were then classified for individual flight lines (to be used for relative accuracy testing and calibration). Software: TerraScan v.11.007
• 5. Using ground classified points per each flight line, the relative accuracy was tested. Automated line-to-line calibrations were then performed for system attitude parameters (pitch, roll, heading), mirror flex (scale) and GPS/IMU drift. Calibrations were performed on ground classified points from paired flight lines. Every flight line was used for relative accuracy calibration. Software: TerraMatch v.11.005
• 6. Position and attitude data were imported. Resulting data were classified as ground and non-ground points. Statistical absolute accuracy was assessed via direct comparisons of ground classified points to ground RTK survey data. Data were then converted to orthometric elevations (NAVD83) by applying a Geoid03 correction. Software: TerraScan v.11.007, TerraModeler v.11.002
• 7. Bare Earth models were created as a triangulated surface and exported as ArcInfo ASCII grids at a 1 m pixel resolution. Highest Hit models were created for any class at 1 m grid spacing and exported as ArcInfo ASCII grids. Software: TerraScan v.11.007, ArcMap v. 9.3.1, TerraModeler v.11.002

• Raw DEM's were processed using ArcGIS 10.1 desktop software. Aspect, percent slope, flow accumulation, and hill shade grids were produced using standard methods. 10, 25, and 50 meter contours were produced using generalized 10 meter DEM's and smoothed.