50131
2012 USGS Lidar: Central Virginia Seismic (Louisa County)
va2012_usgs_louisa_m2620_metadata
Data Set
Published / External
49401
Lidar - partner (no harvest)
Project
Completed
2015-07-10
USGS Contract: G10PC00013
Task Order Number: G12PD00264
Prepared for USGS,
Prepared by: Dewberry, 1000 Ashley Blvd., Suite 801, Tampa, Florida 33602-3718
The LiDAR data were processed to a bare-earth digital terrain model (DTM). Detailed breaklines and bare-earth Digital Elevation Models (DEMs) were produced for the project area. Deliverables were produced in both UTM and State Plane coordinates. The data was formatted according to tiles with each UTM tile covering an area of 1,000 meters by 1,000 meters and each State Plane tile covering an area of 2,500 feet by 2,500 feet. A total of 797 UTM tiles and 1,338 State Plane tiles were produced for the project encompassing an area of approximately 277 sq. miles. Classified points include: Class 1 (unclassified), Class 2 (ground), Class 7 (noise), Class 9 (water), Class 10 (ignored ground due to breakline proximity).
The primary purpose of this project was to develop a consistent and accurate surface elevation dataset derived from high-accuracy Light Detection and Ranging (LiDAR) technology for the USGS Louisa, Virginia Project Area.
10775
A footprint of this data set may be viewed in Google Earth at:
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/2620/supplemental/va2012_usgs_louisa_m2620.kmz
A final project report is available at:
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/2620/supplemental/va2012_usgs_louisa_m2620_finalreport.pdf
A qa/qc report is available at:
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/2620/supplemental/va2012_usgs_louisa_m2620_qualityreport.pdf
An acquisition report is available at:
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/2620/supplemental/va2012_usgs_louisa_m2620_acquisitionreport.pdf
Theme
ISO 19115 Topic Category
elevation
Theme
Surface
Theme
Terrain
Temporal
2013
Temporal
March
Office for Coastal Management
Charleston
SC
Data Set
As Needed
las
LiDAR points in LAZ format (Classes 1,2,7,9,10)
none
Any conclusions drawn from the analysis of this information are not the responsibility of USGS, Dewberry, NOAA, the Office for Coastal Management or its partners.
Data Steward
2015-07-10
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Distributor
2015-07-10
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Metadata Contact
2015-07-10
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Point of Contact
2015-07-10
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Ground Condition
-78.14545
-77.71609
38.13649
37.7704
Range
2012-03-09
2012-03-12
Yes
Unclassified
This data can be obtained on-line at the following URL:
https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=2620;
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. These data depict the heights at the time of the survey and are only accurate for that time.
https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=2620
Customized Download
Create custom data files by choosing data area, product type, map projection, file format, datum, etc.
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/2620/index.html
Bulk Download
Simple download of data files.
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/2620/supplemental/va2012_usgs_louisa_m2620.kmz
Browse Graphic
Browse Graphic
kmz
The project area addressed by this report falls within the Virginia county of Louisa with actual data edges falling within Fluvanna, Goochland, and Spotsylvania.
https://coast.noaa.gov
Online Resource
https://coast.noaa.gov/dataviewer
Online Resource
2017-03-20
Date that the source FGDC record was last modified.
2017-11-14
Converted from FGDC Content Standards for Digital Geospatial Metadata (version FGDC-STD-001-1998) using 'fgdc_to_inport_xml.pl' script. Contact Tyler Christensen (NOS) for details.
2018-02-08
Partial upload of Positional Accuracy fields only.
2018-03-13
Partial upload to move data access links to Distribution Info.
Not tested; Quantitative Value: 1.0 meters, Test that produced the value: Not tested, assuming 1.0 m
For the Louisa, Virginia LiDAR Project, all checkpoints were located in Open Terrain land cover type. The tested RMSEz for checkpoints in open terrain equaled 0.07 m compared with the 0.125 m specification; and the FVA computed using RMSEz x 1.9600 was equal to 0.13 m, compared with the 0.245 m specification.
For the Louisa, Virginia LiDAR Project, the tested CVA computed using the 95th percentile was equal to 0.12 m, compared with the 0.363 m specification.; Quantitative Value: 0.13 meters, Test that produced the value: FVA computed using RMSEz x 1.9600 was equal to 13 cm
A visual qualitative assessment was performed to ensure data completeness and bare earth data cleanliness. No void or missing data, the bare earth surface is of good quality and data passes vertical accuracy specifications
Data covers the tile scheme provided for the project area
1
Report completed: August 03, 2012; used as process date below.
LiDAR mass points were produced to LAS 1.2 specifications, including the following LAS classification codes: Class 1 = Unclassified, and used for all other features that do not fit into the Classes 2, 7, 9, or 10, including vegetation, buildings, etc.; Class 2 = Ground, includes accurate LiDAR points in overlapping flight lines; Class 7 = Noise, low and high points; Class 9 = Water, points located within collected breaklines; Class 10 = Ignored Ground due to breakline proximity.
The data was processed using GeoCue and TerraScan software. The initial step is the setup of the GeoCue project, which is done by importing a project defined tile boundary index encompassing the entire project area. The acquired 3D laser point clouds, in LAS binary format, were imported
into the GeoCue project and tiled according to the project tile grid. Once tiled, the laser points were classified using a proprietary routine in TerraScan. This routine classifies any obvious outliers in the dataset to class 7. After points that could negatively affect the ground are removed from class 1, the ground layer is extracted from this remaining point cloud. The ground extraction process encompassed in this routine takes place by building an iterative surface model.
This surface model is generated using three main parameters: building size, iteration angle and iteration distance. The initial model is based on low points being selected by a roaming window with the assumption that these are the ground points. The size of this roaming window is determined by the building size parameter. The low points are triangulated and the remaining points are evaluated and subsequently added to the model if they meet the iteration angle and distance constraints. This process is repeated until no additional points are added within iterations. A second critical parameter is the maximum terrain angle constraint, which determines the maximum terrain angle allowed within the classification model.
The following fields within the LAS files are populated to the following precision: GPS Time (0.000001 second precision), Easting (0.003 meter precision), Northing (0.003 meter precision), Elevation (0.003 meter precision), Intensity (integer value - 12 bit dynamic range), Number of Returns (integer - range of 1-4), Return number (integer range of 1-4), Scan Direction Flag (integer - range 0-1), Classification (integer), Scan Angle Rank (integer), Edge of flight line (integer, range 0-1), User bit field (integer - flight line information encoded). The LAS file also contains a Variable length record in the file header that defines the projection, datums, and units.
2012-08-03T00:00:00
2
Once the initial ground routine has been performed on the data, Dewberry creates Delta Z (DZ) orthos to check the relative accuracy of the LiDAR data. These orthos compare the elevations of LiDAR points from overlapping flight lines on a 1 meter pixel cell size basis. If the elevations of points within each pixel are within 5 cm of each other, the pixel is colored green. If the elevations of points within each pixel are between 5 cm and 10 cm of each other, the pixel is colored yellow, and if the elevations of points within each pixel are greater than 10 cm in difference, the pixel is colored red. Pixels that do not contain points from overlapping flight
lines are colored according to their intensity values. DZ orthos can be created using the full point cloud or ground only points and are used to review and verify the calibration of the data is acceptable. Some areas are expected to show sections or portions of red, including terrain variations, slope changes, and vegetated areas or buildings if the full point cloud is used.
However, large or continuous sections of yellow or red pixels can indicate the data was not calibrated correctly or that there were issues during acquisition that could affect the usability of the data. The DZ orthos for Louisa, Virginia showed that the data was calibrated correctly with no issues that would affect its usability. The figure below shows an example of the DZ orthos.
Dewberry utilized a variety of software suites for data processing. The LAS dataset was received and imported into GeoCue task management software for processing in Terrascan. Each tile was imported into Terrascan and a surface model was created to examine the ground classification. Dewberry analysts visually reviewed the ground surface model and corrected errors in the ground classification such as vegetation, buildings, and bridges that were present following the initial processing conducted by Dewberry. Dewberry analysts employ 3D visualization techniques to view the point cloud at multiple angles and in profile to ensure that non-ground points are removed from the ground classification. After the ground classification corrections were completed, the dataset was processed through a water classification routine that utilizes breaklines compiled by dewberry to automatically classify hydro features. The water classification routine selects ground points within the breakline polygons and automatically classifies them as class 9, water. The final classification routine applied to the dataset selects ground points within a specified distance of the water breaklines and classifies them as class 10, ignored ground due to breakline proximity.
2012-08-03T00:00:00
3
The NOAA Office for Coastal Management (OCM) received the topographic/bathymetric files in LAS format from the University of William and Mary's Center for Geospatial Analysis. A number of LAS files were found to have corrupt GPS times and other unknown factors affecting header information. The files contained lidar easting, northing, elevation, intensity, return number, etc. The data was received in UTM coordinates, zone 18 North, referenced to the NAVD88 for vertical using the Geoid09 model. OCM performed the following processing for data storage and Digital Coast provisioning purposes:
1. The LAS files were converted to geographic horizontal coordinates and ellipsoidal vertical coordinates.
2. The LAS files were cleared of error points and variable length records removed.
2014-07-22T00:00:00
gov.noaa.nmfs.inport:50131
Anne Ball
2017-11-15T15:24:28
SysAdmin InPortAdmin
2022-08-09T17:11:38
2022-03-16
OCM Partners
OCMP
1002
Public
No
2022-03-16
1 Year
2023-03-16