Data Management Plan

The project area is composed of 16 counties in the State of South Carolina - Cherokee, Union, Laurens,

Greenwood, Newberry, Chester, Fairfield, Lancaster, Chesterfield, Marlboro, Darlington, Dillon, Marion,

Williamsburg, Clarendon, and Orangeburg. This metadata file is for the lidar county deliverables for Cherokee County, SC.

The project area consists of approximately 10,194 square miles including a buffer of 50 feet along the edges of the

project area and an additional buffer in some areas. The project design of the lidar data acquisition was developed

to support a nominal post spacing of 1.4 meters. The Fugro EarthData, Inc. acquisition team of Fugro Horizons, Inc.

and North West Group acquired 721 flight lines in 44 lifts from January 15, 2008 through February 10, 2008. The data

was divided into 5000' by 5000' foot cells that serve as the tiling scheme. Lidar data collection was performed with a

Cessna 310 aircraft, utilizing a Leica ALS50-II MPiA sensor, collecting multiple return x, y, and z data as well as

intensity data. Lidar data was processed to achieve a bare ground surface (Classes 2 and 8). Lidar data is remotely

sensed high-resolution elevation data collected by an airborne collection platform. Using a combination of laser range

finding, GPS positioning and inertial measurement technologies, lidar instruments are able to make highly detailed

Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation.

Process Steps:

• 2008-06-17 00:00:00 - 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.
• 2008-11-10 00:00:00 - 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.
• 2008-11-21 00:00:00 - 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.
• 2008-11-23 00:00:00 - 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.
• 2009-09-01 00:00:00 - 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. 3. The LAS header fields were sorted by latitude and updated.

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.

;