Data Management Plan

Continental Mapping Consultants, Inc. (CMC) acquired LiDAR data and imagery for the Tualatin National Wildlife Refuge on May 15, 2012. The project area was expanded to include a 100m buffer around the area of interest to ensure complete coverage. The dataset encompasses 19.24 square miles in the Tualatin National Wildlife Refuge, Wapato, Oregon. The lidar was collected with a pulse density of 30-60 points per square meter. Continental Mapping used co-mounted imagery and lidar sensors and a helicopter to acquire the data.

Process Steps:

• LiDAR Data Acquisition: The LiDAR acquisition mission was flown on May 15, 2012. LiDAR acquisition of the project area consisted of 21 low level flight lines with an average altitude of 375 meters. The imagery acquisition consisted of 9 high level flight lines flown at an average altitude of 860 meters.
• A network of control points was established within the project boundary to validate the accuracy of the LiDAR data. The network consisted of Real Time Kinetic (RTK) points collected by Terra Remote Sensing, and existing US Fish and Wildlife Service monuments. The following points, WP02, WP03, WP06, and WP08 were verified by Terra Remote Sensing against the active CORS control stations, JIME (Portland, OR) and NWBG (Newberg, OR). An additional network check was completed between CORS stations FTS5, GOBS, and P367. Points WP02 and WP08 were also used as an RTK/PPK (Post Processed Kinematic) base station for the collection of lidar and orthophoto checkpoints.
• The raw project LiDAR data was imported, processed, and outputs were created using the TerraScan software suite. Automated ground filters were run on the raw las data. These filters include factors and settings such as max building size, terrain angle, iteration angle degrees to plane, iteration distance to plane, reduce iteration angle when edge length is less than, and stop triangulation when edge length is less than. After the automated ground filter is run each tile is than checked for spikes and anomalies. Manual edits are applied to any areas that the analysts interpreted the ground doing something other than what the automatic ground filter interpreted. An analyst also classifies and edits any other las point to needed feature classes at this time. Only the LAS inside the provided map limit was classified and checked by analysts. Any points that were relevant to the classification were classified to the SOW requirements and placed using the classes provided in the SOW. Class 1 Processed, but unclassified, Class 2 Bare-Earth Ground, Class 3 Vegetation, Class 4 Roads, Class 7 Noise, Class 9 Water, Class 10 Ignored Ground, Class 11 Withheld. Classified tiles were saved as las (Version 1.2). After classification and edits were complete the projection information was Geo-Coded back into the LAS files.
• 2019-12-11 00:00:00 - NOAA/OCM received the data from DOGAMI in LAZ format . Data were in NAD83(CORS 96) Oregon Lambert horizontally and NAVD88 (Geoid09) vertically. For ingest into the Digital Coast Data Access Viewer data were converted to geographic coordinates on the GRS80 ellipsoid in meters.

Data is available online for bulk or custom downloads

Data is backed up to tape and to cloud storage.