2018 USGS Lidar: North Slope, AK - QL2

Product: Classified light detection and ranging (lidar) LAS 1.4 files formatted to 4,474 1500 ft x 1500 ft tiles.

In July 2018, Quantum Spatial (QSI) was contracted by the United States Geological Survey (USGS) to collect Light Detection and Ranging (LiDAR) data in the summer of 2018 for several areas of interest (AOIs), comprising the North Slope Borough Communities 3DEP LiDAR project in Alaska. Data were collected to aid USGS in assessing the topographic and geophysical properties of the study area, to support its mission to gather high quality 3D elevation data over the state of Alaska.

Due to inclement weather and the short acquisition timeframe in Alaska, QSI was able to collect LiDAR data in eight out of the eleven contracted AOIs in the 2018 acquisition season: Atqasuk, Barrow North, Barrow South, Barrow Village, Deadhorse, Kaktovic, Nuiqsut and Wainwright. Data collection for the remaining AOIs: Anaktuvuk Pass, Point Lay, and Point Hope was then completed in the summer of 2019.

Dataset Description: The North Slope Borough 3DEP LiDAR project called for the planning, acquisition, and processing of LiDAR data collected at an aggregate nominal pulse spacing (ANPS) of either 0.35 meters or 0.70 meters depending on area. 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 the NAD83(2011) horizontal datum and NAVD88 (GEOID12B) vertical datum. Data was projected in the appropriate Alaska State Plane Zone for its location.

The purpose of the lidar data was to produce a high accuracy 3D dataset that meets all necessary standards laid out by the 3DEP initiative. The raw lidar point cloud data were used to create classified lidar las files, hydroflattened DEMs, highest hit DSMs, intensity images, 2 foot contours, 3D hydro breaklines, and 3D building footprints.

CONTRACTOR: Quantum Spatial, Inc.

Ground Control Points were acquired by Umiaq.

Quantum Spatial coordinated the data acquisition and performed all calibration, follow up processing, and creation of the final derived products.

The following are the USGS lidar fields in JSON:

{

"ldrinfo" : {

"ldrspec" : "U.S. Geological Survey (USGS) - National Geospatial Program (NGP) Lidar Base Specification v1.3",

"ldrsens" : "Leica ALS80",

"ldrmaxnr" : "15",

"ldrnps" : "0.5",

"ldrdens" : "4",

"ldranps" : "0.35",

"ldradens" : "8",

"ldrfltht" : "1750",

"ldrfltsp" : "115",

"ldrscana" : "30",

"ldrscanr" : "58.4",

"ldrpulsr" : "321.4",

"ldrpulsd" : "2.5",

"ldrpulsw" : "0.75",

"ldrwavel" : "1064",

"ldrmpia" : "2",

"ldrbmdiv" : "0.22",

"ldrswatw" : "938",

"ldrswato" : "60",

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

},

"ldrinfo" : {

"ldrspec" : "U.S. Geological Survey (USGS) - National Geospatial Program (NGP) Lidar Base Specification v1.3",

"ldrsens" : "Leica ALS80",

"ldrmaxnr" : "15",

"ldrnps" : "1",

"ldrdens" : "1",

"ldranps" : "0.70",

"ldradens" : "2",

"ldrfltht" : "1750",

"ldrfltsp" : "140",

"ldrscana" : "38",

"ldrscanr" : "53.3",

"ldrpulsr" : "202",

"ldrpulsd" : "2.5",

"ldrpulsw" : "0.75",

"ldrwavel" : "1064",

"ldrmpia" : "1",

"ldrbmdiv" : "0.22",

"ldrswatw" : "1205",

"ldrswato" : "30",

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

},

"ldraccur" : {

"ldrchacc" : "0.5",

"rawnva" : "0.042",

"rawnvan" : "45",

"clsnva" : "0.042",

"clsnvan" : "45",

"clsvva" : "0.154",

"clsvvan" : "24"

},

"lasinfo" : {

"lasver" : "1.4",

"lasprf" : "6",

"laswheld" : "Withheld (ignore) 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" : "3",

"clasitem" : "Low Vegetation (0.5-2 meters)"

},

"lasclass" : {

"clascode" : "4",

"clasitem" : "Medium Vegetation (2-6 meters)"

},

"lasclass" : {

"clascode" : "5",

"clasitem" : "High Vegetation (6+ meters)"

},

"lasclass" : {

"clascode" : "6",

"clasitem" : "Buildings"

},

"lasclass" : {

"clascode" : "7",

"clasitem" : "Noise"

},

"lasclass" : {

"clascode" : "9",

"clasitem" : "Water"

},

"lasclass" : {

"clascode" : "17",

"clasitem" : "Bridge Decks"

},

"lasclass" : {

"clascode" : "20",

"clasitem" : "Ignored Ground"

},

"lasclass" : {

"clascode" : "21",

"clasitem" : "Snow"

}

}}

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

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.

Absolute accuracy was assessed using Non-Vegetated Vertical Accuracy (NVA) reporting designed to meet guidelines presented in the FGDC National Standard for Spatial Data Accuracy. NVA compares known ground check point data that were withheld from the calibration and post-processing of the LiDAR point cloud to the triangulated surface generated by the unclassified LiDAR point cloud as well as the derived gridded bare earth DEM. NVA is a measure of the accuracy of LiDAR point data in open areas where the LiDAR system has a high probability of measuring the ground surface and is evaluated at the 95% confidence interval (1.96 * RMSE).

The mean and standard deviation (sigma ) of divergence of the ground surface model from quality assurance point coordinates are also considered during accuracy assessment. These statistics assume the error for x, y and z is normally distributed, and therefore the skew and kurtosis of distributions are also considered when evaluating error statistics. For the North Slope Borough Communities survey, 56 ground check points were withheld from the calibration and post processing of the LiDAR point cloud, with resulting non-vegetated vertical accuracy of 0.140 feet (0.043 meters) as compared to unclassified LAS, and 0.139 feet (0.042 meters) as compared to the bare earth DEM, with 95% confidence. NVA of unclassified LAS files RMSE = 0.072 ft (0.022 m).

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 data passes Non-Vegetated Vertical Accuracy specifications.

Data covers the entire area specified for this delivery 1 area.

Data is backed up to tape and to cloud storage.