2017 SC DNR Lidar: Georgetown County
OCM Partners
Data Set
(DS)
| ID: 57114
| Published / External
Created: 2019-08-05
|
Last Modified: 2023-10-17
Project (PRJ) | ID: 49401
ID: 57114
Data Set (DS)
* Discovery• First Pass
» Metadata Rubric
Item Identification
* » Title | 2017 SC DNR Lidar: Georgetown County |
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Short Name | sc2017_geotown_m8794_metadata.xml |
* Status | Completed |
Creation Date | |
Revision Date | |
• Publication Date | 2018-03 |
* » Abstract |
Precision Aerial Reconnaissance (PAR) collected 902 square miles in the South Carolina county of Georgetown. 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 1100 LAS tiles and 1100 DEM tiles were produced for the entire project. The NOAA Office for Coastal Management (OCM) received 1100 las files from the South Carolina DNR and processed the data 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 available for download at the link in the Related Items section of this metadata record. 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. |
* 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. |
Notes | |
Other Citation Details | |
• Supplemental Information |
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" : "0.098", "rawnvan" : "43", "clsnva" : "0.098", "clsnvan" : "43", "clsvva" : "0.180", "clsvvan" : "46" }, "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" } }} |
DOI (Digital Object Identifier) | |
DOI Registration Authority | |
DOI Issue Date |
Keywords
Theme Keywords
Thesaurus | Keyword |
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Global Change Master Directory (GCMD) Science Keywords | EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION |
Global Change Master Directory (GCMD) Science Keywords | EARTH SCIENCE > OCEANS > COASTAL PROCESSES > COASTAL ELEVATION |
ISO 19115 Topic Category | elevation |
None | Bare earth |
None | beach |
None | erosion |
Temporal Keywords
Thesaurus | Keyword |
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* Spatial Keywords
Thesaurus | Keyword |
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Global Change Master Directory (GCMD) Location Keywords | CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > SOUTH CAROLINA |
Global Change Master Directory (GCMD) Location Keywords | VERTICAL LOCATION > LAND SURFACE |
Stratum Keywords
Thesaurus | Keyword |
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Instrument Keywords
Thesaurus | Keyword |
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Global Change Master Directory (GCMD) Instrument Keywords | LIDAR > Light Detection and Ranging |
Platform Keywords
Thesaurus | Keyword |
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Global Change Master Directory (GCMD) Platform Keywords | Airplane > Airplane |
Physical Location
• » Organization | Office for Coastal Management |
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• » City | Charleston |
• » State/Province | SC |
• Country | |
• » Location Description |
Data Set Information
* Data Set Scope Code | Data Set |
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• Data Set Type | Elevation |
• Maintenance Frequency | As Needed |
Maintenance Note | |
» Data Presentation Form | Model (digital) |
• Entity Attribute Overview | |
Entity Attribute Detail Citation | |
Entity Attribute Detail URL | |
Distribution Liability |
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 Set Credit | Dewberry, SC DNR |
Support Roles
* » Support Role | Data Steward |
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* » Date Effective From | 2019 |
Date Effective To | |
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 |
Fax | |
Mobile | |
URL | https://coast.noaa.gov |
Business Hours | |
Contact Instructions |
* » Support Role | Distributor |
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* » Date Effective From | 2019 |
Date Effective To | |
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 |
Fax | |
Mobile | |
URL | https://coast.noaa.gov |
Business Hours | |
Contact Instructions |
* » Support Role | Metadata Contact |
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* » Date Effective From | 2019 |
Date Effective To | |
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 |
Fax | |
Mobile | |
URL | https://coast.noaa.gov |
Business Hours | |
Contact Instructions |
* » Support Role | Point of Contact |
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* » Date Effective From | 2019 |
Date Effective To | |
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 |
Fax | |
Mobile | |
URL | https://coast.noaa.gov |
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* Contact Instructions |
Extents
Currentness Reference | Ground Condition |
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Extent Group 1
Extent Description |
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Extent Group 1 / Geographic Area 1
* » W° Bound | -79.687357 |
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* » E° Bound | -78.99431 |
* » N° Bound | 33.787475 |
* » S° Bound | 33.101837 |
* » Description |
Extent Group 1 / Vertical Extent
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Extent Group 1 / Time Frame 1
* » Time Frame Type | Range |
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* » Start | 2016-12-16 |
End | 2017-03-09 |
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Description |
Spatial Information
Spatial Resolution
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Equivalent Scale Denominator | |
Level of Detail Description |
Spatial Representation
Grid Representation Used? | No |
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Vector Representation Used? | Yes |
Text / Table Representation Used? | No |
TIN Representation Used? | No |
Stereo Model Representation Used? | No |
Video Representation Used? | No |
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Point Object Present? | Yes |
Point Object Count | 17087029931 |
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Reference Systems
Reference System
EPSG Code | EPSG:6319 | ||||||||||||||||||||||||||||
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Access Information
Data License | |
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Data License URL | |
Data License Statement | |
* » Security Class | Unclassified |
* Security Classification System | |
Security Handling Description | |
• Data Access Policy | |
» Data Access Procedure |
Data is available online for bulk and 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. |
Metadata Access Constraints | |
Metadata Use Constraints |
Distribution Information
Start Date | 2019-08-05 |
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End Date | Present |
» Download URL | https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=8794 |
Distributor | NOAA Office for Coastal Management (NOAA/OCM) (2019 - Present) |
File Name | Customized Download |
Description |
Create custom data files by choosing data area, product type, map projection, file format, datum, etc. A new metadata will be produced to reflect your request using this record as a base. |
File Date/Time | |
File Type (Deprecated) | Zip |
Distribution Format | |
File Size | |
Application Version | |
Compression | Zip |
Review Status |
Start Date | 2019-08-05 |
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End Date | Present |
» Download URL | https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/8794/index.html |
Distributor | NOAA Office for Coastal Management (NOAA/OCM) (2019 - Present) |
File Name | Bulk Download |
Description |
Bulk download of data files in LAZ format, geographic coordinates, orthometric heights. Note that the vertical datum (hence elevations) of the files here are different than described in this document. |
File Date/Time | |
File Type (Deprecated) | LAZ |
Distribution Format | LAS/LAZ - LASer |
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Compression | Zip |
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Archive Information
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URLs
URL | https://coast.noaa.gov/dataviewer/ |
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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 | https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/8794/supplemental/sc2017_georgetown_m8794.kmz |
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Name | Browse graphic |
URL Type | Browse Graphic |
File Resource Format | KML |
Description |
This graphic displays the footprint for this lidar data set. |
URL | https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/8794/supplemental/Appendix_A_Checkpoint_Survey_Report.pdf |
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Name | Dataset report |
URL Type | Online Resource |
File Resource Format | |
Description |
Link to data set survey report. |
URL | https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/8794/supplemental/South_Carolina_Lidar_Georgetown_Report_180615.pdf |
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Name | Dataset report |
URL Type | Online Resource |
File Resource Format | |
Description |
Link to data set report. |
URL | https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/8794/breaklines/ |
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URL Type | Online Resource |
File Resource Format | |
Description |
Link to data set breaklines. |
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Technical Environment
Description |
Microsoft Windows 7 Enterprise Service Pack 1; ESRI ArcCatalog 10.3 |
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Data Quality
Representativeness | |
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Accuracy | |
Analytical Accuracy | |
Horizontal Positional Accuracy |
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. |
Vertical Positional Accuracy |
The vertical accuracy of the source lidar and final bare earth DEMs was tested by Dewberry with 101 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 (26), and urban terrain (24), and vegetated terrain, including forest (16), brush (17), tall weeds, crops, and high grass (18). The vertical accuracy of the lidar 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. The vertical accuracy of the final bare earth DEMs 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. Accuracy results may vary between the source lidar and final DEM deliverable. DEMs are created by averaging several lidar points within each pixel which may result in slightly different elevation values at each survey checkpoint when compared to the source LAS, which is tested by comparing survey checkpoints to TINs. TINs do not average several lidar points together but interpolate (linearly) between two or three points to derive an elevation value. The accuracy results reported for the overall project are the accuracy results of the source lidar. Bare earth DEM accuracy results are reported in the DEM metadata file. All checkpoints located in non-vegetated terrain were used to compute the Non-vegetated Vertical Accuracy (NVA). Project specifications required a NVA of 0.64 ft (19.6 cm) at the 95% confidence level based on RMSEz (0.33 ft/10 cm) x 1.9600. All checkpoints located in vegetated terrain were used to compute the Vegetated Vertical Accuracy (VVA). Project specifications required a VVA of 0.96 ft (29.4 cm) based on the 95th percentile. This lidar dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 0.33 ft (10 cm) RMSEz Vertical Accuracy Class. Actual NVA accuracy was found to be RMSEz =0.20 ft (6.1 cm), equating to +/- 0.40 ft (12.2 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). |
Quantitation Limits | |
Bias | |
Comparability | |
Completeness Measure | |
Precision | |
Analytical Precision | |
Field Precision | |
Sensitivity | |
Detection Limit | |
Completeness Report |
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. |
Conceptual Consistency |
Data covers the project boundary. |
» Quality Control Procedures Employed |
Data Management
» Have Resources for Management of these Data Been Identified? | Yes |
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» Approximate Percentage of Budget for these Data Devoted to Data Management | Unknown |
» Do these Data Comply with the Data Access Directive? | Yes |
» Is Access to the Data Limited Based on an Approved Waiver? | |
» If Distributor (Data Hosting Service) is Needed, Please Indicate | |
» Approximate Delay Between Data Collection and Dissemination | |
» If Delay is Longer than Latency of Automated Processing, Indicate Under What Authority Data Access is Delayed | |
» Actual or Planned Long-Term Data Archive Location | NCEI-CO |
» Approximate Delay Between Data Collection and Archiving | |
» How Will the Data Be Protected from Accidental or Malicious Modification or Deletion Prior to Receipt by the Archive? |
Data is backed up to tape and to cloud storage. |
Lineage
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Process Steps
Process Step Number | 1 |
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» Description |
Data for the South Carolina Georgetown County Lidar Project was acquired by Precision Aerial Reconnaissance (PAR). The project area included approximately 873 contiguous square miles or 2261 square kilometers for the county of Georgetown in South Carolina. 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 | 2017-12-01 00:00:00 |
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Process Step Number | 2 |
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» 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 | 2017-12-01 00:00:00 |
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The NOAA Office for Coastal Management (OCM) received 1100 las files from the SC DNR. The lidar data had elevation and intensity measurements. The data were in State Plane South Carolina (NAD83 2011) coordinates (Int Feet) and NAVD88 (Geoid12B) elevations in feet. The data were classified as: 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 . OCM processed all classifications of points to the Digital Coast Data Access Viewer (DAV). Classes available on the DAV are: 1, 2, 6, 7, 8, 9, 10, 13, 17, 18. OCM performed the following processing on the data for Digital Coast storage and provisioning purposes: 1. The las files were converted from las to laz format using LASTools laszip. 2. An internal OCM script was run to check the number of points by classification and by flight ID and the gps and intensity ranges. 3. Internal OCM scripts were run on the laz files to convert from orthometric (NAVD88) elevations to ellipsoid elevations using the Geoid 12B model, to convert from State Plane South Carolina (NAD83 2011) coordinates in international feet to geographic coordinates, to convert vertical units from feet to meters, to assign the geokeys, to sort the data by gps time, and zip the data to database and to http. |
Process Date/Time | 2019-07-31 00:00:00 |
Process Contact | Office for Coastal Management (OCM) |
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Data Set (DS) | Cross Reference |
2017 SC DNR Lidar DEM: Georgetown County Hydroflattened Digital Elevation Model (DEM) mission, derived from this Lidar dataset. |
Catalog Details
Catalog Item ID | 57114 |
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Metadata Record Created By | Rebecca Mataosky |
Metadata Record Created | 2019-08-05 10:02+0000 |
Metadata Record Last Modified By | SysAdmin InPortAdmin |
» Metadata Record Last Modified | 2023-10-17 16:12+0000 |
Metadata Record Published | 2022-03-16 |
Owner Org | OCMP |
Metadata Publication Status | Published Externally |
Do Not Publish? | N |
Metadata Workflow State | Published / External |
Metadata Last Review Date | 2022-03-16 |
Metadata Review Frequency | 1 Year |
Metadata Next Review Date | 2023-03-16 |
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