2017 OLC Lidar DEM: Baker County, OR

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This graphic displays the footprint for this lidar data set.

Link to data set report.

This data source was used to populate the lidar point cloud data.

This data source was used (along with the airborne GPS/IMU Data) to aid in the georeferencing of the lidar point cloud data.

This data source was used (along with the lidar intensity imagery) to QC and vertically adjust the lidar point cloud data.

Lidar Pre-Processing: Airborne GPS and IMU data were merged to develop a Single Best Estimate (SBET) of the lidar system trajectory for each lift. Lidar ranging data were initially calibrated using previous best parameters for this instrument and aircraft. Relative calibration was evaluated using advanced plane-matching analysis and parameter corrections derived. This was repeated iteratively until residual errors between overlapping swaths, across all project lifts, was reduced to acceptable levels. Data were then block adjusted to match surveyed calibration control. Raw data NVA were checked using independently surveyed checkpoints. Swath overage points were identified and tagged within each swath file.

Lidar Post-Processing: The calibrated and controlled lidar swaths were processed using automatic point classification routines in proprietary software. These routines operate against the entire collection (all swaths, all lifts), eliminating character differences between files. Data were then distributed as virtual tiles to experienced lidar analysts for localized automatic classification, manual editing, and peer-based QC checks. Supervisory QC monitoring of work in progress and completed editing ensured consistency of classification character and adherence to project requirements across the entire project area.

All classification tags are stored in the original swath files.

After completion of classification and final QC approval, the NVA for the project is calculated. Sample areas for each land cover type present in the project area were extracted and forwarded to the U.S. Geological Survey, for Vegetated Vertical Accuracy (VVA) accuracy tests. Upon acceptance, the complete classified lidar swath files were delivered to the U.S. Geological Survey.

Classified LAS Processing: The bare earth surface is then manually reviewed to ensure correct classification on the Class 2 (Ground) points. After the bare-earth surface is finalized, it is then used to generate all hydro-breaklines through heads-up digitization.

All ground (ASPRS Class 2) LiDAR data inside of the Lake Pond and Double Line Drain hydro flattening breaklines were then classified to water (ASPRS Class 9) using TerraScan macro functionality. A buffer of 0.35 meters was also used around each hydro-flattened feature to classify these ground (ASPRS Class 2) points to Ignored ground (ASPRS Class 10). All Lake Pond Island and Double Line Drain Island features were checked to ensure that the ground (ASPRS Class 2) points were reclassified to the correct classification after the automated classification was completed.

All overlap data was processed through automated functionality provided by TerraScan to classify the overlapping flight line data to approved classes by USGS. The overlap data was classified to Class 18 (High Noise) and Class 129 (Overlap Ground). These classes were created through automated processes only and were not verified for classification accuracy. Due to software limitations within TerraScan, these classes were used to trip the withheld bit within various software packages.

All data was manually reviewed and any remaining artifacts removed using functionality provided by TerraScan and TerraModeler. ArcMap us used as a final check of the bare earth dataset. QSI proprietary software was then used to create the deliverable industry-standard LAS files. QSI proprietary software was used to perform final statistical analysis of the classes in the LAS files, on a per tile level to verify final classification metrics and full LAS header information.

Hydro Flattening Breakline Processing:

Class 2 LiDAR was used to create a bare earth surface model. Proprietary software utilized rasters created within Bentley Microstation to auto-generate breaklines of inland streams and rivers with a 30 meter nominal width which were then manually inspected and digitized. Breaklines for Lakes with surface area greater than 2 acres were generated using heads-up digitization.

Elevation values were assigned to all Inland Ponds and Lakes within ESRI ArcMap; Inland Pond and Lake Islands, Inland Stream and River Islands were assigned elevation values from within ESRI ArcMap.

All ground (ASPRS Class 2) LiDAR data inside of the collected inland breaklines were then classified to water (ASPRS Class 9) using TerraScan macro functionality. A buffer of 0.35 meters was also used around each hydro-flattened stream. These points were moved from ground (ASPRS Class 2) to Ignored Ground (ASPRS Class 10).

The breakline files were then translated to ESRI File-Geodatabase format using ESRI conversion tools.

Hydro Flattened Raster DEM Process:

Class 2 LiDAR in conjunction with the hydro breaklines were used to create a hydro-flattened DEM. Using automated scripting routines within Bentley Microstation, ascii files were created for each tile. The ascii files are then mosaicked together in ArcMap and reviewed for surface anomalies.

The NOAA Office for Coastal Management (OCM) received 1,838 IMG files from the Oregon Lidar Consortium/ DOGAMI. The data were in UTM Zone 11N (NAD83 2011) coordinates in meters and NAVD88 (Geoid12b) elevations in meters, at 1-m spatial resolution.

OCM converted the files from .IMG format to Geotiff format using gdal_warp. The files were then assigned the EPSG codes of 6340 (horizontal) and 5703 (vertical) and then copied to https for Digital Coast storage and provisioning purposes.