2008 South Carolina Lidar: Chester County

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 Chester 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.

The purpose of this project is to collect and deliver topographic elevation point data derived from multiple

return light detection and ranging (lidar) measurements for a 16-county area in South Carolina. The elevation data will

be used as base data for South Carolina's flood plain mapping program (as part of FEMA's Map Modernization

Program) and for additional geospatial map products in the future.

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The LiDAR Quality Assurance (QA) Report Chester County, South Carolina may be viewed at:

https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/511/supplemental/LiDAR_QAQC_Report_Chester.pdf

The information contained in the LAS point cloud data set are the following attributes; X, Y, Z to two significant digits;

Intensity as integer; Class as integer; Return number; Number of returns; Scan direction; scan angle rank; GPS time.

Lidar point cloud data tiled in LAS 1.1 format; ASPRS classification scheme, 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.

Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, 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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Users should be aware that temporal changes may have occurred since this data set was collected and some parts of

this data may no longer represent actual surface conditions. Users should not use this data for critical applications without a

full awareness of its limitations.

The following methods are used to assure lidar accuracy:

1. Use of IMU and ground control network utilizing GPS techniques

2. Use of airborne GPS in conjunction with the acquisition of lidar

3. Measurement of quality control ground survey points within the finished product.

The boresight of the lidar was processed against the ground control for Chester County which consisted of

9 lidar ground survey points and 1 airborne GPS (ABGPS) base station at the operation airport. The horizontal datum

for the control was the North American Datum of 1983, 2007 adjustment (NAD83/2007). The vertical datum was

the North American Vertical Datum of 1988 (NAVD88). The Geoid 2003 model was used to transform the

ellipsoidal heights to GPS derived orthometric heights. ABGPS data was collected during the acquisition mission

for each flight line. During the data acquisition the Positional Dilution of Precision (PDOP) for the ABGPS

was monitored. The control points were measured by technicians using Terrascan and Fugro EarthData

proprietary software and applied to the boresight solution for the project lines.

The minimum expected horizontal accuracy was tested during the boresight process to meet or exceed the

National Standard for Spatial Data Accuracy (NSSDA). Horizontal accuracy is 1 meter RMSE or better.

101 high accuracy checkpoints were surveyed following FEMA Guidelines and Specifications for Flood Hazard Mapping

Partners Appendix A: Guidance for Aerial mapping and Surveying which is based on the NSSDA.

Compared with the 0.363m specification for vertical accuracy at the 95% confidence level, equivalent to 2-foot contours,

the dataset passes by all methods of accuracy assessment (tested by Dewberry):

Tested 0.154 meter Fundamental Vertical Accuracy at 95 percent confidence level in open terrain using

RMSEz x 1.9600 (FEMA/NSSDA and NDEP/ASPRS methodologies);

Tested 0.174 meter Consolidated Vertical Accuracy at 95th percentile in all land cover categories

combined (NDEP/ASPRS methodology);

Tested 0.183 meter Supplemental Vertical Accuracy at 95th percentile in Vegetated terrain (NDEP/ASPRS methodology);

Tested 0.143 meter Supplemental Vertical Accuracy at 95th percentile in Urban terrain (NDEP/ASPRS methodology).

Cloud Cover: 0

The bare earth surface will contain voids where insufficient energy was reflected from the surface to generate a valid

return from the terrain. Voids in the bare earth surface tend to occur in heavily vegetated areas, water bodies, and

beneath buildings, motor vehicles, bridges etc. Fresh or wet asphalt, wet sand and certain types of vegetation can

also cause voids or anomalous elevations.

Compliance with the accuracy standard was ensured by the collection of GPS ground control during the acquisition

of aerial lidar and the establishment of a GPS base station operation airport. The following checks were performed.

1. The ground control and airborne GPS data stream were validated through a fully analytical boresight adjustment.

2. The Lidar elevation data were checked against the project control.

3. Lidar elevation data was validated through an inspection of edge matching and visual inspection for quality

(artifact removal).