2018 AK DGGS Lidar: Sitka, Alaska

Create custom data files by choosing data area, product type, map projection, file format, datum, etc. A new metadata will be produced to reflect your request using this record as a base. Change to an orthometric vertical datum is one of the many options.

Bulk download of data files in LAZ format, geographic coordinates, orthometric heights. Note that the vertical datum (hence elevations) of the files here are different than described in this document. They will be in an orthometric datum.

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.

Link to the lidar report.

Link to view the point cloud (using the Entwine Point Tile (EPT) format) in the 3D Potree viewer.

Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud.

This graphic displays the footprint for this lidar data set.

Link to custom download, from the Data Access Viewer (DAV), the raster Digital Elevation Model (DEM) data that were created from this lidar data set.

Airborne survey - The lidar survey was conducted with a Riegl VUX1-LR lidar scanner with an integrated GNSS and Northrop Grumman IMU system. The integration was designed by Phoenix LiDAR systems. This survey was flown with a pulse rate between 200,000-400,000 pulses/second and at a scan rate between 80 and 150 revolutions/second. This survey was flown with an average elevation of 400 m above ground level and a ground speed of approximately 40 m/s with a fixed-wing Cessna 185 aircraft. The scan angle was set from 55 to 305 degrees, centered normal to the aircraft's bottom. The accompanying report provides additional detail regarding flight conditions.

Ground survey - Trimble R8 and R9 RTK GPS systems were used to collect 195 survey points, 100 of which were used as control points and 95 of which were used as checkpoints. Points were gathered by vehicle along the road system and by boat along the coastline. Points were adjusted for accuracy according to OPUS corrections in Trimble Business Center.

Lidar dataset processing - SDCImport software was used to apply range thresholding, reflectance thresholding, and missed-time-around (MTA) disambiguation for preliminary point cloud noise filtering. In-flight IMU and GNSS data were coupled using Inertial Explorer software to produce the trajectory data. Spatial Explorer software was used to couple the trajectory data with the point cloud. The point cloud data were calibrated using tielines for roll, pitch, and yaw of the aircraft during the survey. This process was first run using all points, then on a per-flightline basis for additional accuracy. Interswath fluctuations in ground points were identified using overlapping tielines to further calibrate the data. The point cloud was classified in accordance with American Society for Photogrammetry and Remote Sensing (ASPRS) guidelines using project-tailored macros. Misclassified points were manually reclassified in post-processing QA/QC. The point cloud was converted from ellipsoidal to orthometric heights using geoid 12B, then uniformly adjusted to maintain a mean offset of 0 with collected ground control. Calibration, classification, and height adjustments were all executed in TerraSolid. Derived products were processed in ArcMap. DTM and DSM were produced using point triangulation with nearest-neighbor interpolation. The DTM was derived from all returns for ground classified points, while the DSM used first returns for all non-noise classes. The CHM was created by subtracting DTM height values from DSM height values. A lidar intensity image was created from first returns of all classes using mean binning.

The NOAA Office for Coastal Management (OCM) downloaded 263 laz files from the Alaska Division of Geological and Geophysical Surveys Elevation Portal (https://elevation.alaska.gov/). The files contained classified elevation and intensity measurements for the 2018 Sitka Alaska project. The data were in UTM Zone 8 NAD83 (2011), meters coordinates and NAVD88 (GEOID12B) elevations in meters. During processing, OCM noted that there are points that fall on water bodies and buildings that are classified as ground. The data had the following classifications: 1 - Unclassified, 2 - Ground, 3- Low Vegetation, 4 - Medium Vegetation, 5 - High Vegetation, 6 - Building, 7 - Noise. OCM processed all points to the Digital Coast Data Access Viewer (DAV).

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

1. Internal OCM scripts were run to check the number of points by classification and by flight ID and the gps and intensity ranges.

2. Internal OCM scripts were run on the laz files to convert from UTM Zone 8 NAD83 (2011), meters coordinates to geographic coordinates, to convert from NAVD88 elevations to ellipsoid elevations using the GEOID12B model, to assign the geokeys, to sort the data by gps time, zip the data to database, and to create Cloud Optimized Point Cloud (COPC) version laz files that are available from the AWS S3 bucket.