2015 USGS Lidar: Eastern Shore VA

Leading Edge Geomatics (LEG) collected 994 square miles in the Virginia counties of Accomack and Northampton. 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: 0-Never Classified, 1-Unclassified, 2-Ground (bare earth points identified as Model Key Points are flagged with the Model Key Point bit), 7-Low Noise, 9-Water, 10-Ignored Ground due to breakline proximity, 17- Bridge Decks, 18-High Noise. Because the Eastern Shore Virginia LiDAR project includes data from the Sandy Topobathy project, there are also topobathy point classifications. They are: 23 - Sensor noise, 24 - Refracted sensor noise, 25 - Water column, 26 - Bathymetric bottom, 27 - Water Surface. Classes 28, 29, and 151 were also included, but after discussion with Dewberry, were determined to be noise classes that should be disregarded. NOAA Office for Coastal Management processed all classifications of points to the Digital Coast Data Access Viewer (DAV), but have made the topobathy noise points unavailable. Classes available from the DAV are: 1, 2, 7, 9, 10, 17, 18, 25, 26, 27.

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 VBMP tile naming convention with each tile covering an area of 5,000 feet by 5,000 ft. A total of 1375 LAS tiles and 1310 DEM tiles were produced for the entire project.

The NOAA Office for Coastal Management (OCM) downloaded this lidar data from the USGS site: ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/NED/LPC/projects/USGS_LPC_VA_Eastern_ShoreBAA_2015_LAS_2017/ and processed the data to be available on the Digital Coast Data Access Viewer (DAV).

In addition to these lidar point data, the breakline data are also available. These data are are available for download at the link provided in the URL section of this metadata record. 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.

Loaded by FGDC Metadata Uploader, batch 10315, 12-15-2017 09:16

The following FGDC sections are not currently supported in InPort, but were preserved and will be included in the FGDC export:

- Spatial Reference Information (FGDC:spref),

- Spatial Data Organization Information (FGDC:spdoinfo)

A complete description of this dataset is available in the Final Project Report that was submitted to the U.S. Geological Survey.

The following are the USGS lidar fields in JSON:

{

"lidar" : {

"ldrinfo" : {

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

"ldrsens" : "Riegl 680i",

"ldrmaxnr" : "7",

"ldrnps" : "0.66",

"ldrdens" : "2.25",

"ldranps" : "0.53",

"ldradens" : "3.45",

"ldrfltht" : "1000",

"ldrfltsp" : "100",

"ldrscana" : "60",

"ldrscanr" : "78",

"ldrpulsr" : "200",

"ldrpulsd" : "5",

"ldrpulsw" : "0.89",

"ldrwavel" : "1064",

"ldrmpia" : "0",

"ldrbmdiv" : "5.0",

"ldrswatw" : "1155",

"ldrswato" : "50",

"ldrgeoid" : "National Geodetic Survey (NGS) Geoid12A"

},

"ldraccur" : {

"ldrchacc" : "0.196",

"rawnva" : "0.118",

"rawnvan" : "59",

"clsnva" : "0.122",

"clsnvan" : "61",

"clsvva" : "0.177",

"clsvvan" : "52"

},

"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" : "0",

"clasitem" : "Calibrated, never classified"

},

"lasclass" : {

"clascode" : "1",

"clasitem" : "Processed, but unclassified"

},

"lasclass" : {

"clascode" : "2",

"clasitem" : "Bare earth, ground (includes model key point bit for points identified as Model Key Point)"

},

"lasclass" : {

"clascode" : "7",

"clasitem" : "Low noise"

},

"lasclass" : {

"clascode" : "9",

"clasitem" : "Water"

},

"lasclass" : {

"clascode" : "10",

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

},

"lasclass" : {

"clascode" : "17",

"clasitem" : "Bridge decks"

},

"lasclass" : {

"clascode" : "18",

"clasitem" : "High noise"

}

}

}}

LiDAR points in LAS 1.4 format

none

This data was produced for the U.S. Geological Survey according to specific project requirements. This information is provided "as is". Further documentation of this data can be obtained by contacting: USGS, 1400 Independence Road, Rolla, MO 65401. Telephone (573) 308-3810.

Any conclusions drawn from the analysis of this information are not the responsibility of Leading Edge Geomatics, Dewberry & Davis the US Geological Survey, the NOAA Office for Coastal Management, or its partners.

This data can be obtained on-line at the following URL: https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=8445

None

This data was produced for the U.S. Geological Survey according to specific project requirements. This information is provided "as is". Further documentation of this data can be obtained by contacting: USGS, 1400 Independence Road, Rolla, MO 65401. Telephone (573)308-3810.

Users should be aware that temporal changes may have occurred since this data set was collected and that some parts of these data may no longer represent actual surface conditions. Users should not use these 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. Dewberry tested the horizontal accuracy of the LiDAR by comparing photo-identifiable survey checkpoints to the LiDAR Intensity Imagery. As only seventeen (17) checkpoints were photo-identifiable, the results are not statistically significant enough to report as a final tested value but the results of this testing are shown below. Using NSSDA methodology (endorsed by the ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014)), horizontal accuracy at the 95% confidence level (called ACCURACYr) is computed by the formula RMSEr * 1.7308 or RMSExy * 2.448. Actual positional accuracy of this dataset was found to be RMSEx = 0.83 ft (25 cm) and RMSEy = 0.91 ft (28 cm) which equates to +/- 2.13 ft (65 cm) at 95% confidence level.

The vertical accuracy of the LiDAR was tested by Dewberry with 113 independent survey checkpoints. The survey checkpoints are evenly distributed throughout the project area and are located in areas of non-vegetated terrain (61 checkpoints), including bare earth, open terrain, and urban terrain, and vegetated terrain (52 checkpoints), including forest, brush, tall weeds, crops, and high grass. 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. 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 =0.21 ft (6.40 cm), equating to +/- 0.41 ft (12.5 cm) at 95% confidence level.

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 entire tile scheme provided for the project area.