2017 SC DNR Lidar: Coastal Counties (Berkeley, Charleston and Williamsburg Counties)

Axis Geospatial collected 1265 square miles in the South Carolina county of Berkeley, and 1124 sq miles in Charleston County. Precision Aerial Reconnaissance collected 965 square miles in Williamsburg county. The nominal pulse spacing for this project was 1 point every 0.7 meters. Dewberry used proprietary procedures to classify the LAS according to project specifications: 1-Unclassified, 2-Ground, 7-Low Noise, 8-Model Keypoints, 9-Water, 10-Ignored Ground due to breakline proximity, 13-Culverts, 17- Bridge Decks, 18-High Noise. Dewberry produced 3D breaklines and combined these with the final lidar data to produce seamless hydro flattened DEMs for the project area. The data was formatted according to the SC DNR tile naming convention with each tile covering an area of 5,000 feet by 5,000 ft.

The NOAA Office for Coastal Management (OCM) downloaded 1526 Berkeley laz files, 1419 Charleston laz files, and 1178 Williamsburg laz files from this USGS site, ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/.

Files downloaded:

1. USGS_LPC_SC_Berkeley_2016_LAS_2019/

2. USGS_LPC_SC_Charleston_2016_LAS_2019/

3. USGS_LPC_SC_Williamsburg_2016_LAS_2019/

The data were processed to the Data Access Viewer (DAV) and https. In addition to the lidar point data, bare earth Digital Elevation Models (DEMs), at a 2.5 foot grid spacing, created from the lidar point data are also available in the Related Items section below. Breakline data are also available. These data are available for download at the link provided in the URL section of this metadata record. Please note that these products have not been reviewed by the NOAA Office for Coastal Management (OCM) and any conclusions drawn from the analysis of this information are not the responsibility of NOAA or OCM.

The purpose of this lidar data was to produce high accuracy 3D elevation products, including tiled lidar in LAS 1.4 format, 3D breaklines, and 2.5 foot cell size hydro flattened Digital Elevation Models (DEMs). All products follow and comply with USGS Lidar Base Specification Version 1.2.

A complete description of this dataset is available in the Final Project Report that was submitted to the SC DNR.

The following are the USGS lidar fields in JSON:

{

"ldrinfo" : {

"ldrspec" : "USGS-NGP Lidar Base Specification V1.2",

"ldrsens" : "Riegl Q1560",

"ldrmaxnr" : "Unlimited",

"ldrnps" : "0.70",

"ldrdens" : "2.00",

"ldranps" : "0.70",

"ldradens" : "2.00",

"ldrfltht" : "2043",

"ldrfltsp" : "150",

"ldrscana" : "58.52",

"ldrscanr" : "169",

"ldrpulsr" : "800",

"ldrpulsd" : "3",

"ldrpulsw" : "0.9",

"ldrwavel" : "1064",

"ldrmpia" : "1",

"ldrbmdiv" : "0.25",

"ldrswatw" : "2289",

"ldrswato" : "30",

"ldrcrs" : "NAD 1983 (2011) State Plane South Carolina International Feet",

"ldrgeoid" : "National Geodetic Survey (NGS) Geoid12B"

},

"ldraccur" : {

"ldrchacc" : "0.196",

"rawnva" : "0.110",

"rawnvan" : "77",

"clsnva" : "0.116",

"clsnvan" : "77",

"clsvva" : "0.213",

"clsvvan" : "72"

},

"lasinfo" : {

"lasver" : "1.4",

"lasprf" : "6",

"laswheld" : "Withheld points were identified in these files using the standard LAS Withheld bit",

"lasolap" : "Swath overage points were identified in these files using the standard LAS overlap bit",

"lasintr" : "16",

"lasclass" : {

"clascode" : "1",

"clasitem" : "Processed, but unclassified"

},

"lasclass" : {

"clascode" : "2",

"clasitem" : "Bare earth, ground"

},

"lasclass" : {

"clascode" : "7",

"clasitem" : "Low noise"

},

"lasclass" : {

"clascode" : "8",

"clasitem" : "Model Keypoints"

},

"lasclass" : {

"clascode" : "9",

"clasitem" : "Water"

},

"lasclass" : {

"clascode" : "10",

"clasitem" : "Ignored ground due to breakline proximity"

},

"lasclass" : {

"clascode" : "13",

"clasitem" : "Culverts"

},

"lasclass" : {

"clascode" : "17",

"clasitem" : "Bridge decks"

},

"lasclass" : {

"clascode" : "18",

"clasitem" : "High noise"

}

}}

Any conclusions drawn from the analysis of this information are not the responsibility of SC DNR, NOAA, the Office for Coastal Management or its partners.

Data is available online for bulk and custom downloads.

None

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.

Microsoft Windows 7 Enterprise Service Pack 1; ESRI ArcCatalog 10.3

Only checkpoints photo-identifiable in the intensity imagery can be used to test the horizontal accuracy of the lidar. Photo-identifiable checkpoints in intensity imagery typically include checkpoints located at the ends of paint stripes on concrete or asphalt surfaces or checkpoints located at 90 degree corners of different reflectivity, e.g. a sidewalk corner adjoining a grass surface. The xy coordinates of checkpoints, as defined in the intensity imagery, are compared to surveyed xy coordinates for each photo-identifiable checkpoint. These differences are used to compute the tested horizontal accuracy of the lidar. As not all projects contain photo-identifiable checkpoints, the horizontal accuracy of the lidar cannot always be tested. Lidar vendors calibrate their lidar systems during installation of the system and then again for every project acquired. Typical calibrations include cross flights that capture features from multiple directions that allow adjustments to be performed so that the captured features are consistent between all swaths and cross flights from all directions.

This data set was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 1.35 ft (41 cm) RMSEx/RMSEy Horizontal Accuracy Class which equates to Positional Horizontal Accuracy = +/- 3.28 ft (1 meter) at a 95% confidence level. No (0) checkpoints were photo-identifiable so no horizontal accuracy testing was conducted.

Berkeley:

The vertical accuracy of the classified lidar was tested by Dewberry with 124 independent survey checkpoints. The survey checkpoints are evenly distributed throughout the project area and are located in areas of non-vegetated terrain, including bare earth, open terrain (33), and urban terrain (27), and vegetated terrain, including forest (20), brush (22), tall weeds, crops, and high grass (22). The vertical accuracy is tested by comparing survey checkpoints to a triangulated irregular network (TIN) that is created from the lidar ground points. Checkpoints are always compared to interpolated surfaces created from the lidar point cloud because it is unlikely that a survey checkpoint will be located at the location of a discrete lidar point. TINs do not average several lidar points together but interpolate (linearly) between two or three points to derive an elevation value.

All checkpoints located in non-vegetated terrain were used to compute the Non-vegetated Vertical Accuracy (NVA). All checkpoints located in vegetated terrain were used to compute the Vegetated Vertical Accuracy (VVA). Actual NVA accuracy was found to be RMSEz =0.15 ft (4.6 cm), equating to +/- 0.28 ft (8.5 cm) at 95% confidence level. Actual VVA accuracy was found to be +/- 0.57 ft (17.4 cm) at the 95th percentile.

The 5% outliers consisted of 4 checkpoints that are larger than the 95th percentile. These checkpoints have DZ values ranging between -2.14 ft (-65.2 cm) to 0.67 ft (20.4 cm).</vertacce>

Charleston;

The vertical accuracy of the source lidar was tested by Dewberry with 149 independent survey checkpoints. The survey checkpoints are evenly distributed throughout the project area and are located in areas of non-vegetated terrain, including bare earth, open terrain (41), and urban terrain (36), and vegetated terrain, including forest (17), brush (28), tall weeds, crops, and high grass (27). The accuracy results reported for the overall project are the accuracy results of the source lidar. All checkpoints located in non-vegetated terrain were used to compute the Non-vegetated Vertical Accuracy (NVA). All checkpoints located in vegetated terrain were used to compute the Vegetated Vertical Accuracy (VVA). Actual NVA accuracy was found to be RMSEz =0.20 ft (6.1 cm), equating to +/- 0.38 ft (11.6 cm)) at 95% confidence level. Actual VVA accuracy was found to be +/- 0.70 ft (21.3 cm) at the 95th percentile.

The 5% outliers consisted of 4 checkpoints that are larger than the 95th percentile. These checkpoints have DZ values ranging between 0.74 ft (22.6 cm) to 0.98 ft (29.9 cm).

Williamsburg:

The vertical accuracy of the classified lidar was tested by Dewberry with 89 independent survey checkpoints. The survey checkpoints are evenly distributed throughout the project area and are located in areas of non-vegetated terrain, including bare earth, open terrain(24), and urban terrain (19), and vegetated terrain, including forest(14), brush(16), tall weeds, crops, and high grass (16).

All checkpoints located in non-vegetated terrain were used to compute the Non-vegetated Vertical Accuracy (NVA). All checkpoints located in vegetated terrain were used to compute the Vegetated Vertical Accuracy (VVA). Actual NVA accuracy was found to be RMSEz =0.16 ft (4.9 cm), equating to +/- 0.32 ft (9.8 cm) at 95% confidence level. Actual VVA accuracy was found to be +/- 0.59 ft (18.0 cm) at the 95th percentile.

The 5% outliers consisted of 3 checkpoints that are larger than the 95th percentile. These checkpoints have DZ values ranging between 0.61 ft (18.6 cm) to 0.81 ft (24.7 cm).</vertacce>

A visual qualitative assessment was performed to ensure data completeness and bare earth data cleanliness. No void or missing data and data passes vertical accuracy specifications.

Data covers the project boundary.

Data is backed up to tape and to cloud storage.