2019 USGS Topobathy Lidar: Potomac River, MD

Product: These lidar data are processed Classified LAS 1.4 files, formatted to 247 individual 1000 m x 1000 m tiles; used to create intensity images, land/water interface breaklines and topobathymetric DEMs as necessary.

Geographic Extent: Potomac River and margins in Maryland, West Virginia, and Virginia, covering approximately 39.2 square miles.

Dataset Description: The Maryland Potomac River Topobathymetric Lidar project called for the planning, acquisition, processing and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meter. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, version 1.3. The data was developed based on a horizontal projection/datum of NAD83 (2011), Universal Transverse Mercator zone 18, meters and vertical datum of NAVD88 (GEOID12B), meters. Lidar data was delivered as processed Classified LAS 1.4 files, formatted to 247 individual 1000 m x 1000 m tiles, as tiled Intensity Imagery, and as tiled topobathymetric DEMs; all tiled to the same 1000 m x 1000 m schema. A merged topobathymetric DEM was also delivered.

Ground Conditions: Lidar was collected in October 2019, while no snow was on the ground and rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Dewberry established a total of 39 checkpoints that were used to calibrate the lidar to known ground locations established the project area and assess the vertical accuracy of the data.

To acquire detailed surface elevation data for use in conservation planning, design, research, floodplain mapping, dam safety assessments and elevation modeling, etc. Classified LAS files are used to show the manually reviewed bare earth surface. This allows the user to create Intensity Images, Breaklines and Raster DEM. The purpose of these lidar data was to produce high accuracy 3D hydro-flattened Digital Elevation Model (DEM) with a 1 meter cell size. These lidar point cloud data were used to create intensity images, 3D breaklines, and hydro-flattened DEMs as necessary.

USGS Contract No. G16PC00020

CONTRACTOR: Dewberry Engineers

SUBCONTRACTOR: IIC Technologies

Lidar data were acquired and calibrated by IIC. All follow-on processing was completed by the prime contractor. 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 V1.3",

"ldrsens" : "Leica Hawkeye 4X (Topo Channels)",

"ldrmaxnr" : "15",

"ldrnps" : "0.35",

"ldrdens" : "8",

"ldranps" : "0.35",

"ldradens" : "8",

"ldrfltht" : "400",

"ldrfltsp" : "140",

"ldrscana" : "40",

"ldrscanr" : "140",

"ldrpulsr" : "500",

"ldrpulsd" : "Unreported",

"ldrpulsw" : "Unreported",

"ldrwavel" : "1064",

"ldrmpia" : "0",

"ldrbmdiv" : "0.5",

"ldrswatw" : "280",

"ldrswato" : "30",

"ldrcrs" : "NAD 1983 (2011) UTM Zone 18 Meters",

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

},

"ldrinfo" : {

"ldrspec" : "USGS-NGP Lidar Base Specification V1.3",

"ldrsens" : "Leica Hawkeye 4X (Shallow/Deep Bathy Channels)",

"ldrmaxnr" : "15",

"ldrnps" : "0.71",

"ldrdens" : "2",

"ldranps" : "0.71",

"ldradens" : "2",

"ldrfltht" : "400",

"ldrfltsp" : "140",

"ldrscana" : "40",

"ldrscanr" : "140",

"ldrpulsr" : "35/10",

"ldrpulsd" : "Unreported",

"ldrpulsw" : "Unreported",

"ldrwavel" : "515",

"ldrmpia" : "0",

"ldrbmdiv" : "4",

"ldrswatw" : "280",

"ldrswato" : "30",

"ldrcrs" : "NAD 1983 (2011) UTM Zone 18 Meters",

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

},

"ldraccur" : {

"ldrchacc" : "0",

"rawnva" : "0",

"rawnvan" : "0",

"clsnva" : "0",

"clsnvan" : "0",

"clsvva" : "0",

"clsvvan" : "0"

},

"lasinfo" : {

"lasver" : "1.4",

"lasprf" : "6",

"laswheld" : "Withheld points were identified in these files using the standard LAS Withheld bit",

"lasolap" : "The LAS overlap bit was not utilized for this dataset",

"lasintr" : "16",

"lasclass" : {

"clascode" : "1",

"clasitem" : "Processed, Unclassified"

},

"lasclass" : {

"clascode" : "2",

"clasitem" : "Bare Earth, Ground"

},

"lasclass" : {

"clascode" : "7",

"clasitem" : "Low Noise"

},

"lasclass" : {

"clascode" : "17",

"clasitem" : "Bridge Deck"

},

"lasclass" : {

"clascode" : "18",

"clasitem" : "High Noise"

},

"lasclass" : {

"clascode" : "40",

"clasitem" : "Bathymetric Point"

},

"lasclass" : {

"clascode" : "41",

"clasitem" : "Water Surface"

},

"lasclass" : {

"clascode" : "42",

"clasitem" : "Synthetic Water surface"

},

"lasclass" : {

"clascode" : "45",

"clasitem" : "Water Column"

}

}}

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 and custom downloads.

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.

Leica LSS; Bayesmap; LAStools; Microstation; Terrascan; ArcGIS 10.x; Microsoft Windows 10 Enterprise Service Pack 1

Six checkpoints were determined to be photo-identifiable in the intensity imagery and were used to test the horizontal accuracy of the lidar dataset. As only six checkpoints were photo-identifiable, the results are not statistically significant enough to report as a final tested value. 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. No horizontal accuracy requirements or thresholds were provided for this project. However, lidar datasets are generally calibrated by methods designed to ensure a horizontal accuracy of 1 meter or less at the 95% confidence level.

This data set was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 41 cm RMSEx/RMSEy Horizontal Accuracy Class which equates to Positional Horizontal Accuracy = +/- 1 meter at a 95% confidence level. Six checkpoints were photoidentifiable but do not produce a statistically significant tested horizontal accuracy value. Using this small sample set of photo-identifiable checkpoints, positional accuracy of this dataset was found to be RMSEx = 28.5 cm and RMSEy = 38.5 cm which equates to +/- 82.8 cm at 95% confidence level. While not statistically significant, the results of the small sample set of checkpoints are within the produced to meet horizontal accuracy.

The topographic portion of this lidar dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 10 cm RMSEz Vertical Accuracy Class.

Actual NVA accuracy was found to be RMSEz =3.9 cm, equating to +/- 7.6 cm at 95% confidence level.

Actual VVA accuracy was found to be +/- 5.9 cm at the 95th percentile.

The bathymetric portion of this lidar dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for an 18.5 cm RMSEz Vertical Accuracy Class. Actual bathymetric vertical accuracy was found to be RMSEz = 8.4 cm, equating to +/- 16.5 cm at 95% confidence level.

Topobathymetric data covers the project boundary to the fullest extent possible depending on water clarity, environmental conditions, and sensor signal returns. The raw point cloud is of good quality and data passes Non-Vegetated Vertical Accuracy specifications.

Data covers the entire area specified for this project.

Data is backed up to tape and to cloud storage.

The NOAA Office for Coastal Management (OCM) downloaded this data from the USGS rockyweb site. OCM processed the data to make it available for custom download from the NOAA Digital Coast Data Access Viewer (DAV) and for bulk download from AWS S3.