2006 USFS Lidar DEM: Rogue River - Siskiyou National Forest - Ashland, OR

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Bulk download of data files in UTM Zone 10 (NAD83) coordinates and NAVD88 (Geoid03) elevations in meters.

This graphic displays the footprint for this lidar data set.

Link to data set report.

The LiDAR survey utilized an Opetch ALTM 3100 mounted in the belly of a Cessna Grand Caravan 208B. The survey was conducted on July 1st-4th, 2006 (Julian Days 182-185). Quality control (QC) pre-mission flights were performed based on manufacturer’s specifications prior to the survey. The QC flight was conducted at the Ashland, Oregon Airport using known surveyed control points. The positional accuracy of the LiDAR (x, y, z) returns are checked against these known locations to verify the calibration and to report base accuracy. The Optech ALTM 3100 system was set to acquire 70,000 laser pulses per second (i.e. 70kHz pulse repetition rate) and flown at 1,100 meters above ground level (AGL), capturing a scan angle of +/-14o from nadir1, to yield points with an average density of ≥7.5 points per square meter. The entire area was surveyed with opposing flight line sidelap of 50% (100% overlap) to reduce laser shadowing and increase surface laser painting. The system allows up to four range measurements per pulse, and all laser returns were processed for the output dataset. To solve for laser point position, it is vital to have an accurate description of aircraft position and attitude. Aircraft position is described as x, y and z and measured twice a second (2 Hz) by an onboard differential GPS unit. Aircraft attitude is measured 200 times a second (200 Hz) as pitch, roll and yaw (heading) from an onboard inertial measurement unit (IMU). Throughout the survey, two dual frequency DGPS base stations at monuments placed by Watershed Sciences and corrected by the Online Positioning User Service (OPUS), recorded fast static (1 Hz) data. The fast static ground GPS data were used to calculate a kinematic correction for the aircraft position.

Two Thales Z-max units were used for the ground survey portion of the survey. To collect accurate ground surveyed points, a GPS base unit was set up to broadcast a kinematic correction to a roving GPS unit. The ground crew used a roving unit to receive radio-relayed kinematic corrected positions from the base unit. 859 RTK points were collected throughout the study area and were used to assess the LiDAR data accuracy.

Laser point coordinates were computed using the REALM v. 3.5.2 software suite based on independent data from the LiDAR system (pulse time, scan angle), aircraft attitude, and aircraft position. Laser point returns (first through fourth) are assigned an associated (x, y, z) coordinate, along with unique intensity values (1-255). The data are output into one very large LAS v. 1.0 file format; each point has a corresponding scan angle, return number (echo), intensity, and x,y,z (easting, northing, and elevation) information. The initial laser point file is too large to process. To facilitate laser point processing, bins (polygons) were created to divide the dataset into manageable sizes (less than 500 MB and approximately 1 km2 each). Flight lines and LiDAR data were then reviewed to ensure complete coverage of the study area and positional accuracy of the laser points. These processing bins were ultimately aggregated into areas of 0.9375-minute quadrangles (1/64th of a standard USGS 7.5-minute quadrangle.

Once the laser point data are imported into bins in TerraScan, a manual calibration test is performed to assess the system offsets for pitch, roll, yaw and scale.

Using a geometric relationship developed by Watershed Sciences, each of these offsets is resolved and corrected if necessary. The LiDAR points are then filtered for noise, pits and birds by screening for absolute elevation limits, isolated points and height above ground. Each bin is then inspected for pits and birds manually, and spurious points are removed. For a bin measuring 1 km2, an average of 20-40 points are found to be artificially low or high.

The internal calibration is refined using TerraMatch. Points from overlapping lines are tested for internal consistency and final adjustments are made for system misalignments (i.e. pitch, roll, yaw and scale offsets). Once these misalignments are corrected, GPS drift can then be resolved and removed. The resulting dataset is internally calibrated using both manual and automated routines. At this point in the workflow, remaining data have passed initial screening and are deemed accurate.

The TerraScan software suite is designed specifically for classifying near-ground laser points (Soinenen, 2004). The processing sequence begins by ‘removing’ all points that are not ‘near’ the earth based on evaluation of the multi-return layers. The resulting bare earth (ground) model is visually inspected and additional ground modeling is performed in site specific areas (over a 50 meter radius) to improve ground detail. This is only done in areas with known ground modeling deficiencies, such as: bedrock outcrops, cliffs, deeply incised stream banks, and dense vegetation.

Custom vegetation modeling is also performed using Fusion v.2.1 deforestation algorithms (Haugerud and Harding, 2001; Andersen et al. 2003; McGaughey and Carson, 2003; McGaughey, in progress2).

The ground model rasters were created in TerraScan by creating TINs of the ground points and developing an ArcINFO GRID of the TIN. A raster of the bare ground surface was created at a 1-meter resolution, with z-units (elevation units) in meters. A Fusion v.2.1 5x5 model was used to develop a raster of buildings and vegetation (above ground surfaces) at a 1-meter resolution, with z-units (elevation units) in meters. All rasters were converted to ESRI GRID format and delivered with metadata.

The NOAA Office for Coastal Management (OCM) received 6 raster DEM files in ESRI ArcGrid format from DOGAMI. The data were in UTM Zone 10 (NAD83) coordinates and NAVD88 (Geoid03) elevations in meters. The bare earth raster files were at a 1 m grid spacing.

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

1. Used internal script to assign the EPSG codes (Horiz - 26910, Vert - 5703) and convert to GeoTiff format.

2. Copied the files to https.