2020 USFS Lidar DEM: Middle Fork, North and South Clackamas (OR, WA)

Middle Fork Site

North Clackamas

Detroit Middle Fork

South Clackamas

Time frame of collection based upon the timestamps of the lidar point cloud used to derive the DEM.

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Bulk download of data files in the original coordinate system.

Information on the NOAA Office for Coastal Management (OCM)

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.

Aircraft and Sensor Information and Flight Plan Execution

Atlantic operated a PACDV (N750DV) outfitted with an Optech Galaxy Prime LiDAR system during the collection of the project area. Atlantic acquired 1588 passes of the AOI as a series of perpendicular and/or adjacent flight-lines executed in 44 flight missions conducted between June 29, 2018 and January 24, 2019. Onboard differential Global Navigation Satellite System (GNSS) unit(s) recorded sample aircraft positions at 2 hertz (Hz) or more frequency. LiDAR data was only acquired when a minimum of six (6) satellites were in view.

Ground Control Survey

A total of 198 ground survey points were collected in support of this project. Point cloud data accuracy was tested against a Triangulated Irregular Network (TIN) constructed from LiDAR points in clear and open areas. A clear and open area can be characterized with respect to topographic and ground cover variation such that a minimum of five (5) times than 1/3 of the RMSEZ deviation from a low-slope plane. Slopes that exceed ten (10) percent were avoided. Each land cover type representing ten (10) percent or more of the total project area were tested and reported with a GCP. In land cover categories other than dense urban areas, the tested points did not have obstructions forty-five (45) degrees above the horizon to ensure a satisfactory TIN surface. The GCP value is provided as a target. It is understood that in areas of dense vegetation, swamps, or extremely difficult terrain, this value may be exceeded. The GCP value is a requirement that must be met, regardless of any allowed 'busts' in the VVA(s) for individual land cover types within the project. Checkpoints for the assessment are required to be well-distributed throughout the land cover type, for the entire project area

LiDAR Point Cloud Generation

Atlantic used Leica software products to download the IPAS ABGNSS/IMU data and raw laser scan files from the airborne system. Waypoint Inertial Explorer is used to extract the raw IPAS ABGNSS/IMU data, which is further processed in combination with controlled base stations to provide the final Smoothed Best Estimate Trajectory (SBET) for each mission. The SBETs are combined with the raw laser scan files to export the LiDAR ASCII Standard (*.las) formatted swath point clouds.

LiDAR Calibration

Using a combination of GeoCue, TerraScan and TerraMatch; overlapping swath point clouds are corrected for any orientation or linear deviations to obtain the best fit swath-to-swath calibration. Relative calibration was evaluated using advanced plane-matching analysis and parameter corrections derived. This process was repeated interactively until residual errors between overlapping swaths, across all project missions, was reduced to no more than 2cm. A final analysis of the calibrated lidar is preformed using a TerraMatch tie line report for an overall statistical model of the project area.

Upon completion of the data calibration, a complete set of elevation difference intensity rasters (dZ Orthos) are produced. A user-defined color ramp is applied depicting the offsets between overlapping swaths based on project specifications. The dZ orthos provide an opportunity to review the data calibration in a qualitative manner. Atlantic assigns green to all offset values that fall below the required RMSDz requirement of the project. A yellow color is assigned for offsets that fall between the RMSDz value and 1.5x of that value. Finally, red values are assigned to all values that fall beyond 1.5x of the RMSDz requirements of the project

LiDAR Classification

Multiple automated filtering routines are applied to the calibrated LiDAR point cloud identifying and extracting bare-earth and above ground features. GeoCue, TerraScan, and TerraModeler software was used for the initial batch processing, visual inspection and any manual editing of the LiDAR point clouds. Classified point clouds were cut to match the tile index and its corresponding tile names and delivered in .laz format.

LiDAR Intensity Imagery

LiDAR intensity imagery was created from the final calibrated and classified lidar point cloud. Intensity images were produced from all classified points and posted to a 0.5-meter cell size. Intensity images were cut to match the tile index and its corresponding tile names and delivered in .img format.

Bare-Earth Surface - Digital Elevation Model (DEM)

Bare earth Digital Elevation Models (DEMs) were derived using the bare earth (ground) LiDAR points. All DEMs were created with a grid spacing of 1 meter. DEMs were cut to match the tile index and its corresponding tile names and delivered in .img format.

Data were received from US Forest Service region 6 in Imagine (*.img) format, USFS region 6 Albers projection (meters) and NAVD88 Geoid12b meters vertically. Data were converted to cloud optimized geotiffs for distribution in the Digital Coast Data Access Viewer.

The time of collection listed in process step 1 is noted to be incorrect, but was left as the original metadata record from Atlantic, Inc. Based upon the time stamps in the lidar records, the collection appears to be from July 29, 2020 to August 20, 2020. This suggests that some of the process steps were copied from a different metadata records and may not reliably describe the collection and processing of this dataset.