2010 ARC Carroll County Georgia Lidar

This metadata record describes the DTM comprised of classified aerial lidar

elevation points, photogrammetrically compiled breaklines and the derived TIN for Carroll

County, GA. This dataset contains the following classifications of points:

Class 1 = Unclassified. This class includes vegetation, buildings, noise etc.

Class 2 = Ground

Original contact information:

Contact Name: Peter Debick

Contact Org: Carroll County Community Development

Title: GIS Manager

Phone: 770-830-5861

Email: pdebick@carrollcountyga.com

The lidar DEM data was collected for the Carroll County, GA area. All lidar returns

were classified using the default classes of Terrascan processing software for Unclassified

Points (class 1), Ground points (class 2), Water points (class 9), Overlap points (class 12).

The lidar ground points are supplemented with photogrammmetrically compiled breaklines from

digital imagery collected during the same project time frame as the lidar. The ground class

points, often refered to as "bald earth" are then used as an input to proprietary and publicly

available processing software to generate a Triangulated Irregular Network (TIN) model.

Classified lidar DEMs and derived TIN models are useful for a variety of applications, such

as aiding in contour generation, development of digital surface models, 3D modeling, flood

plane mapping, viewshed analysis and the production of orthophotos.

10372

Support of the FEMA's FIRM program.

A footprint of this data may be viewed in Google Earth at:

https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/2522/supplemental/ga2010_carrollcounty.KMZ

A LiDAR Report from the vendor for this data set may be viewed here:

https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/2522/supplemental/CarrollCo_GA_QCreport.pdf

Any conclusions drawn from the analysis of this information are not the responsibility of

Atlanta Regional Commission, Kucera International, the Office for Coastal Management,

or its partners.

This data can be obtained on-line at the following URL: https://coast.noaa.gov/dataviewer

The data set is dynamically generated based on user-specified parameters.

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In some areas of heavy vegetation or forest cover, there may be relatively few ground points in the LiDAR data.

TINing the points produces large triangles and hence the elevations may be less accurate within such areas.

Elevation values for open water surfaces are not valid elevation values because few LiDAR points are returned

from water surfaces. Triangles were created across water surfaces by interpolating from the nearest land points.

Attribute accuracy is tested in the LiDAR processing stage. After classification of the LiDAR data, the 'bald earth' point class is compared to ground control collected within the project area.

Horizontal positional accuracy for LiDAR is dependent upon the quality of the GPS/INS solution, sensor calibration and ground conditions at the time of data capture. The standard system results for horizontal accuracy are less than 1 meter.; Quantitative Value: 1 meters, Test that produced the value: This value is computed by comparing ground control to an intensity based image derived from the classified LiDAR data and represents the RMSE of residuals on controls within the project area.

Vertical positional accuracy for LiDAR is dependent upon the quality of the GPS/INS solution, sensor calibration and ground conditions at the time of data capture. The vertical accuracy for this project was tested with a resultant RMSE of 0.030 meter (0.099 feet).; Quantitative Value: 0.030 meters, Test that produced the value: This value is computed by comparing ground control elevation to the classified LiDAR ground surface and represents the RMSE of residuals on controls within the project area.

LiDAR data is collected for the project area. Post processing of the simultaneously acquired GPS/INS is performed and applied to the laser returns to output a point cloud in the specified project coordinate system and datums. The point cloud data is then subjected to automated classification routines to assign all points in the point cloud to ground, water, overlap and unclassified point classes. Anomalous laser returns that occur infrequently are removed entirely from the data set. The ground class points are then compared to surveyed ground control to develop an accuracy measure of the laser terrain data.

LiDAR data is collected within the project area, processed and verified against control.