2016 FEMA Lidar DEM, Malheur, OR

Lidar collection dates.

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Information on the NOAA Office for Coastal Management (OCM)

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Link to data set report.

Link to data set report.

This data set is the project specified acquired point cloud data.

This data set is the project specified lidar deliverables.

This data set is the project specified acquired ground control and QAQC control data.

All lidar data were acquired using a Dual-Head DragonEye (DE) sensor owned and operated by GDS installed in a Cessna 401. The sensor was mounted in a Leica PAV100 gyro-stabilized mount integrated with a NovAtel SPAN GNSS and LCI-100C IMU. Real time navigation and GNSS/IMU data logging was provided by Leica FlightPro software. Lidar data were logged on the Airborne Hydrography, AB (AHAB) operator console. A calibration flight was conducted at Nampa Airport, ID on 30 March, 2016. Project data were acquired from 23 March 2016 until 09 April, 2016. Some blocks remained snow covered at this time. Once the snow had cleared, calibration flights were conducted at Nampa Airport, ID on 08 and 09 June, 2016, with the final survey data being acquired on 10 June and 15 June, 2016. Field calibration of the DE system is carried out to eliminate systematic errors by calculating corrections for boresight errors, scanner angle errors, remaining IMU angle errors and any necessary internal timing errors. Initial data coverage analysis and quality checks were performed to ensure there were no potential system issues were carried out in the field prior to demobilization of the sensor. Data were initially processed in Leica’s Lidar Survey Studio (LSS) using final processed trajectory information. LAS files from LSS were imported to a Terrascan project where spatial algorithms were used to remove gross system noise and a basic ground classification was conducted per flight line for Terra Match use. TMatch was then run on the project, and a comparison to the lidar control points was conducted. This calibrated/controlled LAS dataset was then provided to Woolpert for further processing and deliverable production.

Woolpert utilized 2 Trimble Navigation R10 Model GNSS dual-frequency GPS receivers and 1 TSC3 data collector for this project. The field crew utilized Real-Time Kinematic (RTK) and GPS Rapid Static methods throughout the ground control data collection process. Using these observations were performed on a total of 244 points. The survey was conducted using a 1-second epoch rate, in a fixed solution RTK mode, with each observation lasting between 60 to 180 seconds. Each station was occupied twice to insure the necessary horizontal and vertical accuracies were being met for this LiDAR / photogrammetric project.

Once calibration of the flightline data was completed by GDS the data was then provided to Woolpert. The point cloud underwent a classification process to determine bare-earth points and non-ground points utilizing "first and only" as well as "last of many" lidar returns. This process determined Default (Class 1), Ground (Class 2), Low Noise (Class 7), Water (Class 9), Ignored Ground (Class 10), Bridge Decks (Class 17) and High Noise (Class 18). The bare-earth (Class 2 - Ground) lidar points underwent a manual QA/QC step to verify the quality of the DEM as well as a peer-based QC review. This included a review of the DEM surface to remove artifacts and ensure topographic quality. Classification of water (class 9) and ignored ground (class 10) was completed via the use of the hydrologic breaklines collected for the hydro-flattening phase. The overlap classes were determined by first identifying the overlapping areas and reclassifying the LAS data by offset from a corridor. This allows the returns located on the edge of the swath to be removed from the bare earth coverage in an effort to produce a more uniform data density. The returns determined to be overlap including overlap default, ground, water, and ignored ground are then applied an overlap flag and reclassified to their respective standard classification value. 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. The resulting deliverables for this task order consist of classified LAS file in LAS 1.4 format, Raw Swath LAS files in LAS 1.4 format, 0.5 meter pixel size DEM files in ERDAS IMG format, 8-bit Intensity files in GeoTIFF format, Hydrologic and Bridge abutment breakline data in ESRI Geodatabase format. The method used to create the DEM consisted of isolating the ground (class 2) points and introducing 3-d breakline data derived from delineating hydrologic features and bridge breaklines applying USGS v1.2 hydro flattening specification z-values. This combined dataset was then processed into a gridded format for additional QAQC to ensure DEM quality. Following QAQC process completion, a gridded raster file was created on a per tile basis. The task order projection information was applied to the final raster dataset. Prior to delivery, all raster files were visually reviewed to ensure coverage and reviewed using automated processes to ensure proper formatting.

NOAA/OCM received DEM files in IMG format from DOGAMI. Data were in NAD83(2011) UTM 11N horizontally and NAVD88 (Geoid12B) vertically. All units were meters. For ingest into the Digital Coast Data Access Viewer and adhere to the Open Data Policy, data were converted to GeoTiff format.