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Item Identification
Keywords
Physical Location
Data Set Info
Support Roles
Extents
Access Info
Distribution Info
URLs
Tech Environment
Data Quality
Lineage
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Catalog Details

Summary

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Short Citation
OCM Partners, 2024: 2017 SC DNR Lidar DEM: Coastal Counties (Berkeley, Charleston and Williamsburg Counties), https://www.fisheries.noaa.gov/inport/item/57112.
Full Citation Examples

Abstract

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. A total of 1419 LAS tiles were produced for Charleston, 1526 tiles produced for Berkeley and 1178 tiles for Williamsburg County.

The NOAA Office for Coastal Management (OCM) received the DEM files from the South Carolina Department of Natural Resources (SC DNR). The data were in SC State Plane (NAD83 2011) with horizontal units in international feet and NAVD88 (Geoid12B) elevations in U.S. Survey feet. The bare earth hydro-flattened raster files were at a 2.5 ft grid spacing. These were processed to the Data Access Viewer (DAV) and https. Please note that these products have bot 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.

Distribution Information

  • Create custom data files by choosing data area, map projection, file format, etc. A new metadata will be produced to reflect your request using this record as a base.

  • Bulk download of data files in the original coordinate system.

Access Constraints:

None

Use Constraints:

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.

Controlled Theme Keywords

COASTAL ELEVATION, elevation, SEAFLOOR TOPOGRAPHY, TERRAIN ELEVATION

Child Items

No Child Items for this record.

Contact Information

Point of Contact
NOAA Office for Coastal Management (NOAA/OCM)
coastal.info@noaa.gov
(843) 740-1202

Metadata Contact
NOAA Office for Coastal Management (NOAA/OCM)
coastal.info@noaa.gov
(843) 740-1202

Extents

Geographic Area 1

-80.458377° W, -79.264688° E, 33.88967° N, 32.479725° S

Time Frame 1
2016-12-15 - 2017-03-07

Dates of collection for Berkeley County

Time Frame 2
2016-12-15 - 2016-12-30

Dates of collection for Williamsburg County

Time Frame 3
2016-12-16 - 2017-03-09

Dates of collection for Charleston County

Item Identification

Title: 2017 SC DNR Lidar DEM: Coastal Counties (Berkeley, Charleston and Williamsburg Counties)
Short Name: sc2017_cst_counties_dem_m8790
Status: Completed
Creation Date: 2019-08-01
Publication Date: 2018-07
Abstract:

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. A total of 1419 LAS tiles were produced for Charleston, 1526 tiles produced for Berkeley and 1178 tiles for Williamsburg County.

The NOAA Office for Coastal Management (OCM) received the DEM files from the South Carolina Department of Natural Resources (SC DNR). The data were in SC State Plane (NAD83 2011) with horizontal units in international feet and NAVD88 (Geoid12B) elevations in U.S. Survey feet. The bare earth hydro-flattened raster files were at a 2.5 ft grid spacing. These were processed to the Data Access Viewer (DAV) and https. Please note that these products have bot 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.

Purpose:

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.

Supplemental Information:

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

Keywords

Theme Keywords

Thesaurus Keyword
Global Change Master Directory (GCMD) Science Keywords
EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION
Global Change Master Directory (GCMD) Science Keywords
EARTH SCIENCE > OCEANS > BATHYMETRY/SEAFLOOR TOPOGRAPHY > SEAFLOOR TOPOGRAPHY
Global Change Master Directory (GCMD) Science Keywords
EARTH SCIENCE > OCEANS > COASTAL PROCESSES > COASTAL ELEVATION
ISO 19115 Topic Category
elevation
UNCONTROLLED
None DEM
None DTM

Spatial Keywords

Thesaurus Keyword
Global Change Master Directory (GCMD) Location Keywords
CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA
Global Change Master Directory (GCMD) Location Keywords
VERTICAL LOCATION > LAND SURFACE
Global Change Master Directory (GCMD) Location Keywords
VERTICAL LOCATION > SEA FLOOR

Instrument Keywords

Thesaurus Keyword
Global Change Master Directory (GCMD) Instrument Keywords
LIDAR > Light Detection and Ranging

Platform Keywords

Thesaurus Keyword
Global Change Master Directory (GCMD) Platform Keywords
Airplane > Airplane
Global Change Master Directory (GCMD) Platform Keywords
DEM > Digital Elevation Model

Physical Location

Organization: Office for Coastal Management
City: Charleston
State/Province: SC

Data Set Information

Data Set Scope Code: Data Set
Data Set Type: Elevation
Maintenance Frequency: As Needed
Data Presentation Form: Elevation Data
Distribution Liability:

***

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

Data Set Credit: *** Dewberry

Support Roles

Data Steward

CC ID: 866414
Date Effective From: 2019
Date Effective To:
Contact (Organization): NOAA Office for Coastal Management (NOAA/OCM)
Address: 2234 South Hobson Ave
Charleston, SC 29405-2413
Email Address: coastal.info@noaa.gov
Phone: (843) 740-1202
URL: https://coast.noaa.gov

Distributor

CC ID: 866413
Date Effective From: 2019
Date Effective To:
Contact (Organization): NOAA Office for Coastal Management (NOAA/OCM)
Address: 2234 South Hobson Ave
Charleston, SC 29405-2413
Email Address: coastal.info@noaa.gov
Phone: (843) 740-1202
URL: https://coast.noaa.gov

Metadata Contact

CC ID: 866415
Date Effective From: 2019
Date Effective To:
Contact (Organization): NOAA Office for Coastal Management (NOAA/OCM)
Address: 2234 South Hobson Ave
Charleston, SC 29405-2413
Email Address: coastal.info@noaa.gov
Phone: (843) 740-1202
URL: https://coast.noaa.gov

Point of Contact

CC ID: 866416
Date Effective From: 2019
Date Effective To:
Contact (Organization): NOAA Office for Coastal Management (NOAA/OCM)
Address: 2234 South Hobson Ave
Charleston, SC 29405-2413
Email Address: coastal.info@noaa.gov
Phone: (843) 740-1202
URL: https://coast.noaa.gov

Extents

Currentness Reference: Ground Condition

Extent Group 1

Extent Group 1 / Geographic Area 1

CC ID: 1292274
W° Bound: -80.458377
E° Bound: -79.264688
N° Bound: 33.88967
S° Bound: 32.479725

Extent Group 1 / Time Frame 1

CC ID: 1292271
Time Frame Type: Range
Start: 2016-12-15
End: 2017-03-07
Description:

Dates of collection for Berkeley County

Extent Group 1 / Time Frame 2

CC ID: 1292272
Time Frame Type: Range
Start: 2016-12-15
End: 2016-12-30
Description:

Dates of collection for Williamsburg County

Extent Group 1 / Time Frame 3

CC ID: 1292273
Time Frame Type: Range
Start: 2016-12-16
End: 2017-03-09
Description:

Dates of collection for Charleston County

Access Information

Security Class: Unclassified
Data Access Procedure:

Data is available online for custom downloads

Data Access Constraints:

None

Data Use Constraints:

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.

Distribution Information

Distribution 1

CC ID: 866420
Start Date: 2019-08-01
End Date: Present
Download URL: https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=8790
Distributor: NOAA Office for Coastal Management (NOAA/OCM) (2019 - Present)
File Name: Customized Download
Description:

Create custom data files by choosing data area, map projection, file format, etc. A new metadata will be produced to reflect your request using this record as a base.

File Type (Deprecated): Zip
Compression: Zip

Distribution 2

CC ID: 866421
Start Date: 2019-08-01
End Date: Present
Download URL: https://noaa-nos-coastal-lidar-pds.s3.us-east-1.amazonaws.com/dem/SC_Coast_Counties_DEM_2017_8790/index.html
Distributor: NOAA Office for Coastal Management (NOAA/OCM) (2019 - Present)
File Name: Bulk Download
Description:

Bulk download of data files in the original coordinate system.

URLs

URL 1

CC ID: 866406
URL: https://coast.noaa.gov/
Name: NOAA's Office for Coastal Management (OCM) website
URL Type:
Online Resource
File Resource Format: HTML
Description:

Information on the NOAA Office for Coastal Management (OCM)

URL 2

CC ID: 866407
URL: https://coast.noaa.gov/dataviewer/
Name: NOAA's Office for Coastal Management (OCM) Data Access Viewer (DAV)
URL Type:
Online Resource
File Resource Format: HTML
Description:

The Data Access Viewer (DAV) allows a user to search for and download elevation, imagery, and land cover data for the coastal U.S. and its territories. The data, hosted by the NOAA Office for Coastal Management, can be customized and requested for free download through a checkout interface. An email provides a link to the customized data, while the original data set is available through a link within the viewer.

URL 3

CC ID: 866408
URL: https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid12b/8789/supplemental/sc2017_cst_counties_m8789.kmz
Name: Browse graphic
URL Type:
Browse Graphic
File Resource Format: KML
Description:

This graphic displays the footprint for this lidar data set.

URL 4

CC ID: 866409
URL: https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid12b/8789/supplemental/
Name: Dataset report
URL Type:
Online Resource
File Resource Format: PDF
Description:

Link to data set reports.

URL 5

CC ID: 867197
URL: https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid12b/8789/breaklines/
Name: Breaklines
URL Type:
Online Resource
Description:

The location of breaklines and breakline metadata for each county.

Technical Environment

Description:

Microsoft Windows 7 Enterprise Service Pack 1; ESRI ArcCatalog 10.3

Data Quality

Horizontal Positional Accuracy:

The DEMs are derived from the source lidar and 3D breaklines created from the lidar. Horizontal accuracy is not performed on the DEMs or breaklines.

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. Qualitative value: 3.28 ft (100 cm), Test that produced the valued: The DEMs are derived from the source lidar and 3D breaklines created from the lidar. Horizontal accuracy is not performed on the DEMs or breaklines. 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.

Vertical Positional Accuracy:

The DEMs are derived from the source lidar and 3D breaklines created from the lidar. The DEMs are created using controlled and tested methods to limit the amount of error introduced during DEM production so that any differences identified between the source lidar and final DEMs can be attributed to interpolation differences. DEMs are created by averaging several lidar points within each pixel which may result in slightly different elevation values at a given location when compared to the source LAS, which is tested by comparing survey checkpoints to a triangulated irregular network (TIN) that is created from the lidar ground points. TINs do not average several lidar points together but interpolate (linearly) between two or three points to derive an elevation value.

Berkeley:

The vertical accuracy of the final bare earth DEMs was tested by Dewberry with 124 independent 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(34), 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 extracting the elevation of the pixel that contains the x/y coordinates of the checkpoint and comparing these DEM elevations to the surveyed elevations.

Actual NVA accuracy was found to be RMSEz =0.15 ft (4.6 cm), equating to +/- 0.29 ft (8.8 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 -2.08 ft (-63.4 cm) and 0.68 ft (20.7 cm).

Charleston:

The vertical accuracy of the final bare earth DEMs was tested by Dewberry with 147 independent checkpoints. The same checkpoints that were used to test the source lidar data were used to validate the vertical accuracy of the final DEM products. The survey checkpoints are evenly distributed throughout the project area and are located in areas of non-vegetated terrain, including bare earth, open terrain (40), and urban terrain (36), and vegetated terrain, including forest (16),brush (28), tall weeds, crops, and high grass (27). The vertical accuracy is tested by extracting the elevation of the pixel that contains the x/y coordinates of the checkpoint and comparing these DEM elevations to the surveyed elevations.

Actual NVA accuracy was found to be RMSEz =0.19 ft (5.8 cm), equating to +/- 0.37 ft (11.3 cm) at 95% confidence level. Actual VVA accuracy was found to be +/- 0.73 ft (22.3 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 0.71 ft (21.6 cm) to 1.07 ft (32.6 cm).

Williamsburg:

The vertical accuracy of the final bare earth DEMs was tested by Dewberry with 89 independent 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). The vertical accuracy is tested by extracting the elevation of the pixel that contains the x/y coordinates of the checkpoint and comparing these DEM elevations to the surveyed elevations.

Actual NVA accuracy was found to be RMSEz =0.19 ft (5.8 cm), equating to +/- 0.37 ft (11.3 cm) at 95% confidence level. Actual VVA accuracy was found to be +/- 0.73 ft (22.3 cm) at the 95th percentile.

The 5% outliers consisted of 2 checkpoints that are larger than the 95th percentile. These checkpoints have DZ values ranging between 0.87 ft (26.5 cm) to 1.25 ft (38.1 cm).

Completeness Report:

A visual qualitative assessment was performed to ensure data completeness and full tiles. No void or missing data exists.

Conceptual Consistency:

Data covers the project boundary.

Lineage

Process Steps

Process Step 1

CC ID: 1292259
Description:

Data for the South Carolina Charleston and Berkeley Counties Lidar Project was acquired by Axis Geospatial. Precision Aerial Reconnaissance acquired data for Williamsburg County.

The project area included approximately 1124 contiguous square miles or 2911.1 square kilometers for the county of Charleston in South Carolina,1265 square miles in the county of Berkeley and 965 square miles in Williamsburg County.

Lidar sensor data were collected with the Riegl Q1560 lidar system. The data was delivered in the State Plane coordinate system, international feet, South Carolina, horizontal datum NAD83, vertical datum NAVD88, U.S. Survey Feet, Geoid 12B. Deliverables for the project included a raw (unclassified) calibrated lidar point cloud, survey control, and a final acquisition/calibration report.

The calibration process considered all errors inherent with the equipment including errors in GPS, IMU, and sensor specific parameters. Adjustments were made to achieve a flight line to flight line data match (relative calibration) and subsequently adjusted to control for absolute accuracy. Process steps to achieve this are as follows:

Rigorous lidar calibration: all sources of error such as the sensor's ranging and torsion parameters, atmospheric variables, GPS conditions, and IMU offsets were analyzed and removed to the highest level possible. This method addresses all errors, both vertical and horizontal in nature. Ranging, atmospheric variables, and GPS conditions affect the vertical position of the surface, whereas IMU offsets and torsion parameters affect the data horizontally. The horizontal accuracy is proven through repeatability: when the position of features remains constant no matter what direction the plane was flying and no matter where the feature is positioned within the swath, relative horizontal accuracy is achieved.

Absolute horizontal accuracy is achieved through the use of differential GPS with base lines shorter than 25 miles. The base station is set at a temporary monument that is 'tied-in' to the CORS network. The same position is used for every lift, ensuring that any errors in its position will affect all data equally and can therefore be removed equally.

Vertical accuracy is achieved through the adjustment to ground control survey points within the finished product. Although the base station has absolute vertical accuracy, adjustments to sensor parameters introduces vertical error that must be normalized in the final (mean) adjustment.

The withheld and overlap bits are set and all headers, appropriate point data records, and variable length records, including spatial reference information, are updated in GeoCue software and then verified using proprietary Dewberry tools.

Process Date/Time: 2017-10-01 00:00:00

Process Step 2

CC ID: 1292262
Description:

Dewberry utilizes a variety of software suites for inventory management, classification, and data processing. All lidar related processes begin by importing the data into the GeoCue task management software. The swath data is tiled according to project specifications (5,000 ft x 5,000 ft). The tiled data is then opened in Terrascan where Dewberry identifies edge of flight line points that may be geometrically unusable with the withheld bit. These points are separated from the main point cloud so that they are not used in the ground algorithms. Overage points are then identified with the overlap bit. Dewberry then uses proprietary ground classification routines to remove any non-ground points and generate an accurate ground surface. The ground routine consists of three main parameters (building size, iteration angle, and iteration distance); by adjusting these parameters and running several iterations of this routine an initial ground surface is developed. The building size parameter sets a roaming window size. Each tile is loaded with neighboring points from adjacent tiles and the routine classifies the data section by section based on this roaming window size. The second most important parameter is the maximum terrain angle, which sets the highest allowed terrain angle within the model. As part of the ground routine, low noise points are classified to class 7 and high noise points are classified to class 18. Once the ground routine has been completed, bridge decks are classified to class 17 using bridge breaklines compiled by Dewberry. A manual quality control routine is then performed using hillshades, cross-sections, and profiles within the Terrasolid software suite. After this QC step, a peer review is performed on all tiles and a supervisor manual inspection is completed on a percentage of the classified tiles based on the project size and variability of the terrain. After the ground classification and bridge deck corrections are completed, the dataset is processed through a water classification routine that utilizes breaklines compiled by Dewberry to automatically classify hydrographic features. The water classification routine selects ground points within the breakline polygons and automatically classifies them as class 9, water. During this water classification routine, points that are within 1x NPS or less of the hydrographic features are moved to class 10, an ignored ground due to breakline proximity. A final QC is performed on the data. All headers, appropriate point data records, and variable length records, including spatial reference information, are updated in GeoCue software and then verified using proprietary Dewberry tools.

The data was classified as follows:

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

Class 2 = Ground

Class 7= Low Noise

Class 8 = Model Keypoints

Class 9 = Water

Class 10 = Ignored Ground due to breakline proximity

Class 13 = Culverts

Class 17 = Bridge Decks

Class 18 = High Noise

The LAS header information was verified to contain the following:

Class (Integer)

Adjusted GPS Time (0.0001 seconds)

Easting (0.003 m)

Northing (0.003 m)

Elevation (0.003 m)

Echo Number (Integer)

Echo (Integer)

Intensity (16 bit integer)

Flight Line (Integer)

Scan Angle (degree)

Process Date/Time: 2017-10-01 00:00:00

Process Step 3

CC ID: 1292263
Description:

Dewberry used GeoCue software to produce intensity imagery and raster stereo models from the source lidar. The raster resolution was 2.5 feet.

Process Date/Time: 2017-10-01 00:00:00

Process Step 4

CC ID: 1292264
Description:

Lidar intensity stereopairs were viewed in 3-D stereo using Socet Set for ArcGIS softcopy photogrammetric software. The breaklines are collected directly into an ArcGIS file geodatabase to ensure correct topology. The lidargrammetry was performed under the direct supervision of an ASPRS Certified Photogrammetrist. The breaklines were stereo-compiled in accordance with the Data Dictionary.

Inland Lakes and Ponds and Rivers/Streams were collected according to specifications for the South Carolina Charleston County Lidar Project.

Process Date/Time: 2017-10-01 00:00:00

Process Step 5

CC ID: 1292265
Description:

Dewberry digitzed 2D bridge deck polygons from the intensity imagery and used these polygons to classify bridge deck points in the LAS to class 17. As some bridges are hard to identify in intensity imagery, Dewberry then used ESRI software to generate bare earth elevation rasters. Bare earth elevation rasters do not contain bridges. As bridges are removed from bare earth DEMs but DEMs are continuous surfaces, the area between bridge abutments must be interpolated. The rasters are reviewed to ensure all locations where the interpolation in a DEM indicates a bridge have been collected in the 2D bridge deck polygons.

Process Date/Time: 2017-10-01 00:00:00

Process Step 6

CC ID: 1292266
Description:

The bridge deck polygons are loaded into Terrascan software. Lidar points and surface models created from ground lidar points are reviewed and 3D bridge breaklines are compiled in Terrascan. Typically, two breaklines are compiled for each bridge deck-one breakline along the ground of each abutment. The bridge breaklines are placed perpendicular to the bridge deck and extend just beyond the extents of the bridge deck. Extending the bridge breaklines beyond the extent of the bridge deck allows the compiler to use ground elevations from the ground lidar data for each endpoint of the breakline.

Process Date/Time: 2018-01-01 00:00:00

Process Step 7

CC ID: 1292267
Description:

Breaklines are reviewed against lidar intensity imagery to verify completeness of capture. All breaklines are then compared to ESRI terrains created from ground only points prior to water classification. The horizontal placement of breaklines is compared to terrain features and the breakline elevations are compared to lidar elevations to ensure all breaklines match the lidar within acceptable tolerances. Some deviation is expected between hydrographic breakline and lidar elevations due to monotonicity, connectivity, and flattening rules that are enforced on the hydrographic breaklines. Once completeness, horizontal placement, and vertical variance is reviewed, all breaklines are reviewed for topological consistency and data integrity using a combination of ESRI Data Reviewer tools and proprietary tools. Corrections are performed within the QC workflow and re-validated.

Process Date/Time: 2018-01-01 00:00:00

Process Step 8

CC ID: 1292268
Description:

Class 2, ground, and Class 8, model key points, lidar points are exported from the LAS files into an Arc Geodatabase (GDB) in multipoint format. The 3D breaklines, Inland Lakes and Ponds, Rivers/Streams, and Bridge breaklines are imported into the same GDB. An ESRI Terrain is generated from these inputs. The surface type of each input is as follows:

Ground Multipoint: Masspoints

Inland Lakes and Ponds: Hard Replace

Rivers and Streams : Hard Line

Bridge Breaklines : Hard Line

Process Date/Time: 2018-01-01 00:00:00

Process Step 9

CC ID: 1292269
Description:

The ESRI Terrain is converted to a raster. The raster is created using natural neighbors interpolation with a 2.5 foot cell size. The DEM is reviewed with hillshades in both ArcGIS and Global Mapper. Hillshades allow the analyst to view the DEMs in 3D and to more efficiently locate and identify potential issues. Analysts review the DEM for missed lidar classification issues, incorrect breakline elevations, incorrect hydro-flattening, and artifacts that are introduced during the raster creation process.

Process Date/Time: 2018-01-01 00:00:00

Process Step 10

CC ID: 1292260
Description:

The corrected and final DEM is clipped to individual tiles. Dewberry uses a proprietary tool that clips the DEM to each tile located within the final Tile Grid, names the clipped DEM to the Tile Grid Cell name, and verifies that final extents are correct. All individual tiles are loaded into Global Mapper for the last review. During this last review, an analsyt checks to ensure full, complete coverage, no issues along tile boundaries, tiles seamlessly edge-match, and that there are no remaining processing artifacts in the dataset.

Process Date/Time: 2018-01-01 00:00:00

Process Step 11

CC ID: 1292261
Description:

The NOAA Office for Coastal Management (OCM) received the DEM files from the South Carolina Department of Natural Resources (SC DNR). The data were in SC State Plane (NAD83 2011) with horizontal units in international feet and NAVD88 (Geoid12B) elevations in U.S. Survey feet. The bare earth hydro-flattened raster files were at a 2.5 ft grid spacing.

OCM performed the following processing on the data for Digital Coast storage and provisioning purposes:

1. The DEMs were exported from proprietary ESRI File Geodatabase to 32-bit floating point GeoTIFF format using ArcGIS

2. Global Mapper was then used to create tiles from the single, county-wide DEMs

3. Gdal_translate was used to assign the correct EPSG codes to each tiled file

4. The raster files were copied to database and https for Digital Coast storage and provisioning purposes

Process Date/Time: 2019-08-01 00:00:00
Process Contact: Office for Coastal Management (OCM)

Related Items

Item Type Relationship Type Title
Data Set (DS) Cross Reference 2017 SC DNR Lidar: Coastal Counties (Berkeley, Charleston and Williamsburg Counties)

Link the lidar point files

Catalog Details

Catalog Item ID: 57112
GUID: gov.noaa.nmfs.inport:57112
Metadata Record Created By: Rebecca Mataosky
Metadata Record Created: 2019-08-01 15:52+0000
Metadata Record Last Modified By: Kirk Waters
Metadata Record Last Modified: 2024-01-10 19:06+0000
Metadata Record Published: 2024-01-10
Owner Org: OCMP
Metadata Publication Status: Published Externally
Do Not Publish?: N
Metadata Last Review Date: 2022-03-16
Metadata Review Frequency: 1 Year
Metadata Next Review Date: 2023-03-16