Data Management Plan

Watershed Sciences, Inc. (WS) collected Light Detection and Ranging (LiDAR) data of the Klamath River and associated riparian zones from Klamath Falls, Oregon to Happy Camp, California for Woolpert, Inc. Acquisition of the data occurred between February 27th and March 15th, 2010. The total deliverable area, including a 100 m buffer, is 107,547 acres.

The LiDAR survey used a Leica ALS60 laser system. For the Klamath River survey area, the sensor was set to yield an average native pulse density of > 8 points per square meter over terrestrial surfaces. Up to 4 range measurements are possible per pulse, and all discernible laser returns were processed for the output data set. This lidar data was used to create bare-earth DEMs.

OCM received bare-earth hydroflattened DEM files in ESRI GRID format from the Oregon Lidar Consortium. The files were in California State Plane zone 1 projected coordinate system, NAD83 (HARN) and geoid09, with 3-foot horizontal resolution. No metadata came with this data set; information in this record is derived from the accompanying project report, which is linked below. Additionally, the points from which this DEM was derived are available for download, and are linked in the Related Items section below.

Lineage Statement:
Data was collected and processed by Watershed Sciences Inc. and Woolpert and delivered to the Oregon Department of Geology and Mineral Industries (DOGAMI). The data was obtained by NOAA from DOGAMI and ingested into the Digital Coast Data Access Viewer.

Process Steps:

• Acquisition. The LiDAR survey uses a Leica ALS60 laser system mounted on a Cessna Caravan. For the Klamath River survey area, the sensor scan angle was ±13 degrees from nadir1 with a pulse rate designed to yield an average native density (number of pulses emitted by the laser system) of > 8 points per square meter over terrestrial surfaces. All survey areas were surveyed with an opposing flight line side-lap of >50% (>100% overlap). The Leica ALS60 system allows up to four range measurements (returns) per pulse, and all discernible laser returns were processed for the output dataset. 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. (Citation: raw lidar)
• LiDAR survey datasets were referenced to the 1 Hz static ground GPS data collected over pre- surveyed monuments with known coordinates. While surveying, the aircraft collected 2 Hz kinematic GPS data, and the onboard inertial measurement unit (IMU) collected 200 Hz aircraft attitude data. Waypoint GPS v.8.10 was used to process the kinematic corrections for the aircraft. The static and kinematic GPS data were then post-processed after the survey to obtain an accurate GPS solution and aircraft positions. IPAS v.1.35 was used to develop a trajectory file that includes corrected aircraft position and attitude information. The trajectory data for the entire flight survey session were incorporated into a final smoothed best estimated trajectory (SBET) file that contains accurate and continuous aircraft positions and attitudes. 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 v. 1.2 files; each point maintains the corresponding scan angle, return number (echo), intensity, and x, y, z (easting, northing, and elevation) information. The following processing steps were performed on the data: • 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. • 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). • The TerraScan software suite was used for classifying near-ground points (Soininen, 2004). The resulting ground classified points were visually inspected and additional ground point modeling was performed in site-specific areas to improve ground detail.
• Data was obtained by NOAA Office for Coastal Management from DOGAMI. Data were in California State Plane Zone 1 NAD83(HARN) US survey feet with NAVD88 (Geoid09) US Survey feet vertically. Data were converted to geographic coordinates in ellipsoid heights (meters) using the general cartographic transform package subroutines and reversing the application of GEOID09.

Data is available online for custom downloads

Data is backed up to tape and to cloud storage.