2016 USGS Lidar: Chesapeake Bay, VA

Leading Edge Geomatics (LEG) collected 3753 square miles in the Virginia counties of Ablemarle, Buckingham, Cumberland, Powhatan, Augusta, Rockingham, Greene, Fluvanna, Goochland, Nelson, and Appomattox as well as the City of Charlottesville. 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, 7-Low Noise, 8-Model Key Point, 9-Water, 10-Ignored Ground due to breakline proximity, 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 VBMP tile naming convention with each tile covering an area of 5,000 ft by 5,000 ft. A total of 4255 LAS tiles and DEM tiles were produced for the entire project. 444 tiles have been delivered in NAD83 (2011) Virginia State Plane North, U.S. Survey Feet while 3811 tiles have been delivered in NAD83 (2011) Virgina State Plane South, U.S. Survey Feet. All data has a vertical datum of NAVD88 (Geoid12B), U.S. Survey Feet.

Data were subsequently reprocessed to Entwine Point Tile (EPT) format in web mercator projection with vertical meters. The EPT form of the data is used by the NOAA Digital Coast Data Access Viewer, which this metadata record is supporting. Additional processing steps may have been done by the Data Access Viewer and will be recorded in the lineage section.

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 U.S. Geological Survey.

The following are the USGS lidar fields in JSON:

{

"ldrinfo" : {

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

"ldrsens" : "Riegl 680i",

"ldrmaxnr" : "7",

"ldrnps" : "0.66",

"ldrdens" : "2.30",

"ldranps" : "0.66",

"ldradens" : "2.30",

"ldrfltht" : "900",

"ldrfltsp" : "100",

"ldrscana" : "60",

"ldrscanr" : "82",

"ldrpulsr" : "200",

"ldrpulsd" : "5",

"ldrpulsw" : "0.89",

"ldrwavel" : "1064",

"ldrmpia" : "0",

"ldrbmdiv" : "5.0",

"ldrswatw" : "1039",

"ldrswato" : "55",

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

},

"ldraccur" : {

"ldrchacc" : "0.196",

"rawnva" : "0.171",

"rawnvan" : "112",

"clsnva" : "0.168",

"clsnvan" : "115",

"clsvva" : "0.226",

"clsvvan" : "87"

},

"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 Key Point"

},

"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"

}

}}

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This data was produced for the U.S. Geological Survey according to specific project requirements. This information is provided "as is".

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

Data is available online for bulk or custom downloads

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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. Quantitative value: 1.25 ft (38.1 cm), Test that produced the valued: 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 seven (7) 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 = 0.50 ft (15.2 cm) and RMSEy = 0.52 ft (15.8 cm) which equates to +/- 1.25 ft (38.1 cm) at 95% confidence level.

Actual NVA accuracy was found to be RMSEz =0.28 ft (8.53 cm), equating to +/- 0.55 ft (16.8 cm) at 95% confidence level.

Actual VVA accuracy was found to be +/- 0.74 ft (22.6 cm) at the 95th percentile.

The vertical accuracy of the source LiDAR was tested by Dewberry with 202 independent survey checkpoints. The survey checkpoints are evenly distributed throughout the project area and are located in areas of non-vegetated terrain (115 checkpoints), including bare earth, open terrain, and urban terrain, and vegetated terrain (87 checkpoints), including forest, brush, tall weeds, crops, and high grass. The vertical accuracy of the LiDAR was 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 =0.28 ft (8.53 cm), equating to +/- 0.55 ft (16.8 cm) at 95% confidence level. 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 VVA accuracy was found to be +/- 0.74 ft (22.6 cm) at the 95th percentile.

The 5% outliers consisted of 5 checkpoints that are larger than the 95th percentile. These checkpoints have DZ values ranging between -0.75 ft (22.9 cm) and 1.03 ft (31.4 cm).

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 tile scheme provided for the project area.

Data is backed up to cloud storage.