2011 Georgia Department of Natural Resources (GADNR) Environmental Protection Division (EPD) Lidar: Four Counties (Burke, Columbia, Lincoln, and Richmond)

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This graphic shows the lidar coverage for the four Georgia counties in this data set.

Date that the source FGDC record was last modified.

Converted from FGDC Content Standard for Digital Geospatial Metadata (version FGDC-STD-001-1998) using 'fgdc_to_inport_xml.pl' script. Contact Tyler Christensen (NOS) for details.

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The LiDAR data collected for this task order. | Source Geospatial Form: vector digital data | Type of Source Media: disc

Using a Leica LiDAR system, 100 flight lines of high density data, at a nominal pulse spacing (NPS) of 1.0 meter, were collected over

Burke, Lincoln and Richmond Counties, GA (approximately 1,386 square miles). Multiple returns were recorded for each laser pulse along

with an intensity value for each return. A total of six (6) missions were flown on December 13, 14, 17, and 18 in 2011. The geoid used

to reduce satellite derived elevations to orthometric heights was Geoid09. The horizontal datum used for this survey is North American

Datum 1983, Georgia State Plane Coordinate System, East Zone, and expressed in US Survey Feet. The vertical datum used for this survey

is North American Vertical Datum 1988 (NAVD88), and expressed in US Survey Feet. Airborne GPS data was differentially processed and

integrated with the post processed IMU data to derive a smoothed best estimate of trajectory (SBET). The SBET was used to reduce the

LiDAR slant range measurements to a raw reflective surface for each flight line.

System Parameters:

Type of Scanner = Leica

Data Acquisition Height = 6,500-feet AGL

Scanner Field of View = 40 degrees

The Scan Frequency = 41.8 Hertz

Pulse Repetition Rate - 115.6 Kilohertz

Aircraft Speed = 130 Knots

Swath Width = 4,732-feet

Number of Returns Per Pulse = Maximum of 4

Distance Between Flight Lines = 3,289-feet

The Leica ALS50/60 LiDAR systems calibration and performance is verified on a periodic basis using Woolpert's calibration range. The

calibration range consists of a large building and runway. The edges of the building and control points along the runway have been

located using conventional survey methods. Inertial measurement unit (IMU) misalignment angles and horizontal accuracy are calculated

by comparing the position of the building edges between opposing flight lines. The scanner scale factor and vertical accuracy is

calculated through comparison of LiDAR data against control points along the runway. Field calibration is performed on all flight lines

to refine the IMU misalignment angles. IMU misalignment angles are calculated from the relative displacement of features within the

overlap region of adjacent (and opposing) flight lines. The raw LiDAR data is reduced using the refined misalignment angles.

Once the data acquisition and GPS processing phases are complete, the LiDAR data was processed immediately to verify the coverage had

no voids. The GPS and IMU data was post processed using differential and Kalman filter algorithms to derive a best estimate of

trajectory. The quality of the solution was verified to be consistent with the accuracy requirements of the task order.

The individual flight lines were inspected to ensure the systematic and residual errors have been identified and removed. Then, the

flight lines were compared to adjacent flight lines for any mismatches to obtain a homogenous coverage throughout the project area.

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 bare-earth points (Class 2), noise (Class 7), water (Class 9)

ignored ground (Class 10), unclassified data (Class 1), and overlap points (Class 12). The bare-earth (Class 2 - Ground)

LiDAR points underwent a manual QA/QC step to verify that artifacts have been removed from the bare-earth surface. The surveyed ground

control points are used to perform the accuracy checks and statistical analysis of the LiDAR dataset.

Breaklines defining lakes, greater than two acres, and double-line streams, wider than 100 feet (30.5 meters), were compiled using

digital photogrammetric techniques as part of the hydrographic flattening process and provided as a geodatabase containing ESRI

Polyline Z and Polygon Z feature classes. Breaklines defining water bodies and streams were compiled for this task order. The breaklines

were used to perform the hydrologic flattening of water bodies, and gradient hydrologic flattening of double line streams. Lakes,

reservoirs and ponds, at a nominal minimum size of two (2) acres or greater, were compiled as closed polygons. The closed water bodies

were collected at a constant elevation. Rivers and streams, at a nominal minimum width of 100 feet (30.5 meters), were compiled in the

direction of flow with both sides of the stream maintaining an equal gradient elevation. The hydrologic flattening of the LiDAR data

was performed for inclusion in the National Elevation Dataset (NED). For this specific project, NOAA requested that Woolpert define

the Strom Thurmond Reservoir using a contour set to match the water level used for the portion of the reservoir located in Columbia

County. This elevation is 323.55 survey feet. The Columbia county data was acquired several months prior to the Burke, Richmond, and

Lincoln Counties. Due to this, the water levels in the reservoir were different. Woolpert set the contour to 325.55 survey feet and

classified the las and produced the required products using the contour derived Strom Thurmond Reservoir.

The NOAA Office for Coastal Management (OCM) received the files in las format. The files contained lidar elevation and intensity measurements.

The data were in State Plane projection (NAD83, Georgia East), and vertically referenced to NAVD88 using the Geoid 09 model. Both horizontal

and vertical units were in survey feet. OCM performed the following processing for data storage and Digital Coast provisioning purposes:

1. The data were converted from Georgia State Plane coordinates to geographic (NAD83) coordinates.

2. The data were converted from orthometric (NAVD88) heights to ellipsoidal heights (GRS80) using Geoid09.

3. The data were converted from vertical units of survey feet to meters.

4. Elevation outliers were removed.