2008 South Carolina Lidar: Williamsburg County

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Zipped geodatabase of breaklines

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Project report from the lidar contractor.

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The Fugro EarthData, Inc. acquisition team of Fugro Horizons, Inc. and North West Group collected ALS50-II

derived lidar over 16 counties in the State of South Carolina with a 1.4m, nominal post spacing using a

Cessna 310 aircraft. The collection for the entire project area was accomplished from January 15, 2008 through

February 10, 2008 (Flight dates were January 15, 16, 18, 20, 21, 25, 27, 28, 29, 30, 31 and February 2, 3, 4, 7, 8, 10).

The collection was performed using a Leica ALS50-II MPiA lidar system, serial numbers ALS039 and ALS064,

including an inertial measuring unit (IMU) and a dual frequency GPS receiver. This project required 44 lifts of

flight lines to be collected. The lines were flown at an average of 6,000 feet above mean terrain using a

maximum pulse rate frequency of 112,000 pulses per second. The planned maximum baseline length was 50 miles.

| Type of Source Media: external hard drive

ESP under contract to Fugro EarthData, Inc. successfully established ground control for Williamsburg County, SC. A

total of 12 ground control points in Williamsburg County, SC were acquired. GPS was used to establish the control

network. The horizontal datum was the North American Datum of 1983, 2007 adjustment (NAD83/2007). The

vertical datum was the North American Vertical Datum of 1988 (NAVD88).

| Type of Source Media: electronic mail system

The State of South Carolina, Department of Natural Resources provided digital orthophotography covering the

project area in support of this project.

| Type of Source Media: external hard drive

1. Lidar, GPS, and IMU data was processed together using lidar processing software.

2. The lidar data set for each flight line was checked for project area coverage and lidar post spacing was checked

to ensure it meets project specifications.

3. The lidar collected at the calibration area and project area were used to correct the rotational, atmospheric, and

vertical elevation differences that are inherent to lidar data.

4. Intensity rasters were generated to verify that intensity was recorded for each lidar point.

5. Lidar data was transformed to the specified project coordinate system.

6. By utilizing the ground survey data collected at the calibration site and project area, the lidar data was

vertically biased to the ground.

7. Comparisons between the biased lidar data and ground survey data within the project area were evaluated and a

final RMSE value was generated to ensure the data meets project specifications.

8. Lidar data in overlap areas of project flight lines were trimmed and data from all swaths were merged into a single

data set.

9. The data set was trimmed to the digital project boundary including an additional buffer zone of 50 feet (buffer zone

assures adequate contour generation from the DEM).

10.The resulting data set is referred to as the raw lidar data.

1. The raw lidar data was processed through a minimum block mean algorithm, and points were classified as either

bare earth or non-bare earth.

2. User developed "macros" that factor mean terrain angle and height from the ground were used to determine bare

earth point classification.

3. The next phase of the surfacing process was a 2D edit procedure that ensures the accuracy of the automated

feature classification.

4. Editors used a combination of imagery, intensity of the lidar reflection, profiles, and tin-editing software to assess

points.

5. The lidar data was filtered, as necessary, using a quadric error metric to remove redundant points. This

method leaves points where there is a change in the slope of surfaces (road ditches) and eliminates points from evenly

sloped terrain (flat field) where the points do not affect the surface.

6. The algorithms for filtering data were utilized within Fugro EarthData's proprietary software and commercial software

written by TerraSolid.

7. The flight line overlap points were merged back into filtered data set for delivery product.

8. The point cloud data were delivered tiled in LAS 1.1 format; class 12 - flight line overlap points, class 9 - points

in water, class 8 - model-key points, class 2 - ground points, and class 1 - all other.

Lidar intensity images were generated in TerraSolid software. The images are then brought up in Photoshop to

see if a curve is needed to modify the radiometrics and to ensure they match from group to group. Along with looking

for missing coverage and clipping to the boundary, the following steps are run in Photoshop:

1. Flip 0 values to 1

2. Change 3-band images to 1 band

3. Restore GeoTIFF headers. The intensity images were delivered in GeoTIFF format.

Tiled lidar LAS datasets are imported into a single multipoint geodatabase featureclass. Only Ground and

Model-Keypoint are imported. An ArcGIS geodatabase terrain feature class is created using the terrain creation

dialogue provided through ArcCatalog. The multipoint featureclass is imported as mass point features in the

terrain. An overall tile boundary for the county is input as a soft clip feature for the terrain. The terrain pyramid level

resolutions and scales are automatically calculated based on the point coverage for the county.

The NOAA Office for Coastal Management (OCM) received files in LAS format. The files contained lidar intensity and elevation measurements. OCM performed the following processing on the data to make it available within Digital Coast:

1. The data were converted from State Plane, SPCS Zone 3900 coordinates to geographic coordinates.

2. The data were converted from NAVD88 heights to ellipsoid heights using Geoid03.

Georeferencing information in the files was changed from generic NAD83 to NAD83(HARN) 3D. The proper codes were not available during the initial processing. Values of the coordinates were not changed