Process_Description:
The LiDAR data was captured using an Aero Commander 500 Shrike, Piper Navajo 310, and Cessna 320 Skynight (twin-piston), fixed wing aircraft equipped with a LiDAR system. The LiDAR system includes a differential GPS unit and inertial measurement system to provide superior accuracy.
Acquisition parameters:
1. Scanner - ALTM Gemini LiDAR
2. Flight Height - 1700 meters above mean terrain
3. Swath Width - 32 degrees
4. Sidelap - 50%
5. Nominal Post Spacing - 1.2m
GPS and IMU processing parameters:
1. Processing Programs and version - Applanix POSPac, version 4.4
2. Maximum baseline length - Not greater than 40km.
3. Number of base stations during LiDAR collection - A minimum of 3.
4. Max separation between base stations during LiDAR collection - 0.10m
5. IMU processing monitored for consistency and smoothness - Yes.
Point Cloud Processing:
1. Program and version - Optech ASDA Processor
2. Horizontal Datum - NAD83
3. Horizontal Coordinates - WISCRS Brown County, in US Survey Feet.
4. Vertical Datum - NAVD88
5. Geoid Model used to reduce satellite derived elevations to orthometric heights - NGS Geoid09.
LIDAR Processing:
1. Processing Programs and versions - TerraSolid TerraScan (version 010.017), TerraModeler (version 010.005 and TerraMatch (version 010.011) and Intergraph MicroStation (version.08.05.02.55).
2. Point Cloud data is imported to TerraScan in a Microstation V8 (V) CAD environment on a specified 5000 foot by 5000 foot tiling scheme.
3. Analyze the data for overall completeness and consistency. This is to ensure that there are no voids in the data collection.
4. Inspect for calibration errors in the dataset using the TerraMatch software. This is accomplished by sampling the data collected accross all flight lines and classify the idividual lines to ground. The software will use the ground-classified lines to compute corrections (Heading, Pitch, Roll, and Scale).
5. Orientation corrections (i.e. Calibration corrections) are then applied (if needed) to the entire dataset.
6. Automatic and manual ground classification is performed using algorithms with customized parameters to best fit the project area.
7. The Ayres/Aerometric team captured QA/QC points in 'open terrian' land cover category that were used to test the accuracy of the LiDAR ground surface. TerraScan's Output Control Report (OCR) was used to compare the QAQC data to the LIDAR data. This routine searches the LIDAR dataset by X and Y coordinate, finds the closest LIDAR point and compares the vertical (Z) values to the known data collected in the field. Based on the QAQC data, a bias adjustment was determined, and the results were applied to the LIDAR data. A final OCR was performed with a resulting RMSE of 0.308 ft for the project.
8. Once the automatic processing and testing of LiDAR is complete, the bare-earth surface data was closely inspected to insure that proper classification was achieved as part of a Quality Control process.
9. Final deliverables are generated and output to a client specified PLSS tiling scheme.