2020 USGS Lidar: South Coastal Maine (QL2)

Product: These lidar data are processed Classified LAS 1.4 files, formatted to 3274 individual 1500 m x 1500 m tiles; used to create intensity images, 3D breaklines, and hydro-flattened DEMs as necessary.

Geographic Extent: 10 counties in Maine, covering approximately 2610 total square miles.

Dataset Description: The ME_SouthCoastal_1_2020 Work Unit 191382 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 2.1. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 3274 individual 1500 m x 1500 m tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1500 m x 1500 m schema. Continuous breaklines were produced in Esri file geodatabase format.

Ground Conditions: LiDAR was collected in spring 2020, 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, NV5 Geospatial, powered by Quantum Spatial utilized a total of 64 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 151 independent accuracy checkpoints, 86 in Bare Earth and Urban landcovers (86 NVA points), 65 in Tall Weeds categories (65 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process 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 DEMs. The purpose of these LiDAR data was to produce high accuracy 3D hydro-flattened digital elevation models (DEMs) with a 1 meter cell size. These raw LiDAR point cloud data were used to create classified LiDAR LAS files, intensity images, 3D breaklines, and hydro-flattened DEMs as necessary.

CONTRACTOR: NV5 Geospatial, powered by Quantum Spatial

The following are the USGS lidar fields in JSON:

{

"ldrinfo" : {

"ldrspec" : "USGS-NGP Base Specification v2.1",

"ldrsens" : "Riegl VQ1560i",

"ldrmaxnr" : "unlimited",

"ldrnps" : "0.71",

"ldrdens" : "2.0",

"ldranps" : "0.71",

"ldradens" : "1.98",

"ldrfltht" : "2200",

"ldrfltsp" : "130",

"ldrscana" : "29",

"ldrscanr" : "60",

"ldrpulsr" : "350",

"ldrpulsd" : "3",

"ldrpulsw" : "0.4",

"ldrwavel" : "1064",

"ldrmpia" : "1",

"ldrbmdiv" : "0.18",

"ldrswatw" : "2439.0",

"ldrswato" : "20",

"ldrgeoid" : "Geoid 18",

"ldrcrs" : "NAD 1983 2011 UTM Zone 19N, Meter"

},

"ldraccur" : {

"ldrchacc" : "0",

"rawnva" : "0",

"rawnvan" : "0"

},

"lasinfo" : {

"lasver" : "1.4",

"lasprf" : "6",

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

"lasolap" : "Any overage point deemed geometrically reliable will be used within the normal classification schema. Overage points are not specifically flagged with any special bit value.",

"lasintr" : "16",

"lasclass" : {

"clascode" : "1",

"clasitem" : "Processed, but Unclassified"

},

"lasclass" : {

"clascode" : "2",

"clasitem" : "Bare-Earth Ground"

},

"lasclass" : {

"clascode" : "7",

"clasitem" : "Low Noise"

},

"lasclass" : {

"clascode" : "9",

"clasitem" : "Water"

},

"lasclass" : {

"clascode" : "17",

"clasitem" : "Bridge Decks"

},

"lasclass" : {

"clascode" : "18",

"clasitem" : "High Noise"

},

"lasclass" : {

"clascode" : "20",

"clasitem" : "Ignored Ground"

}

}}

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.

MicroStation Connect; TerraScan Version 20.011; TerraModeler Version 20.004; GeoCue Version 2017.1.14.1; Esri ArcGIS 10.6; Global Mapper 19/20; RiProcess 1.8.5; Windows 10 Operating System

\\point_cloud\tilecls\*.las

Lidar horizontal accuracy is a function of Global Navigation Satellite System (GNSS) derived positional error, flying altitude, and INS derived attitude error. The obtained RMSEr value is multiplied by a conversion factor of 1.7308 to yield the horizontal component of the National Standards for Spatial Data Accuracy (NSSDA) reporting standard where a theoretical point will fall within the obtained radius 95% of the time. Based on a flying altitude of 2200 meters, an IMU error of 0.003 decimal degrees, and a GNSS positional error of 0.064 meters, this project was compiled to meet 0.37 meter horizontal accuracy at the 95% confidence level or 21 cm RMSEr.

This data set was produced to meet ASPRS Positional Accuracy Standard for Digital Geospatial Data (2014) for a 10-cm RMSEz Vertical Accuracy Class.

USGS Determined Vertical Accuracy:

NVA

Number of checkpoints: 86

NVA RMSEz = 4.1 cm, NVA Accuracyz at 95th confidence interval=8.07 cm

VVA

Number of checkpoints: 65

VVA= 13.96 cm at the 95th percentile

For more information see the USGS work package report and the project report. The links to these reports are provided in the URL section of this metadata record.

These LAS data files include all data points collected. No points have been removed or excluded. A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist. The raw point cloud is of good quality and the data pass Non-Vegetated Vertical Accuracy specifications.

Data cover the entire area specified for this project.

Data is backed up to tape and to cloud storage.

The NOAA Office for Coastal Management (OCM) ingested references to the USGS Entwine Point Tiles (EPT) hosted on Amazon Web Services (AWS) into the Digital Coast Data Access Viewer (DAV). The DAV accesses the point cloud as it resides on AWS under the usgs-lidar-public-container.