2017 USGS Lidar: Olympic Peninsula, WA

In August 2017, Quantum Spatial (QSI) was contracted by the United States Geological Survey (USGS) to collect Light Detection and Ranging (LiDAR) data for the Olympic Peninsula 3DEP QL1 LiDAR project site in the state of Washington. The Olympic Peninsula 3DEP LiDAR project area covers approximately 3.4 million acres ( 5,352 square miles) in northwestern Washington split into four areas. The target point density for each study area is ≥8.0 points/m^2 (0.74 points/ft^2).

Ground Conditions: Acquisition below aircraft free of smoke, fog and cloud cover. Ground Control Points were acquired and calibrated by Quantum Spatial, Inc.

Tidal Conditions: The Olympic Peninsula project area is bounded by miles of coastline and includes many tidally influenced lakes and river deltas. Since the project was acquired over many months, it is expected that there is data captured at varying tide levels which lends issues to the hydroflattening process. To accommodate these tidal and temporal differences, it is not uncommon to "stair-step" the flattened water surface to most accurately reflect the different missions in the project while capturing as much ground as permitted. Please reference section C.1.c.(ii).(d) of the task order and the Hydroflattening section of the USGS LiDAR Base Specification, V. 1.2 for more information. Task Name: WA Olympic Peninsula LiDAR 2017 B17, USGS Contract: G16PC00016, Task Order: G17PD00827

The purpose of the lidar data was to produce a high accuracy 3D dataset that meets all necessary standards laid out by the Olympic Peninsula 3DEP contract. The raw lidar point cloud data were used to create classified lidar LAS files, intensity images, hydro-flattened DEMs, and 3D breaklines of rivers, lakes, coastlines and bridges within the study area.

USGS Contract No. G16PC00016

CONTRACTOR: Quantum Spatial, Inc.

Ground Control Points were acquired and calibrated by Quantum Spatial, Inc.

Data acquisition was coordinated by Quantum Spatial. Quantum Spatial, Eagle Aerial, and Airborne Imaging all acquired portions of this project area. All lidar data calibration, and follow-on processing were completed by Quantum Spatial.

The following are the USGS lidar fields in JSON:

{

"ldrinfo" : {

"ldrspec" : "U.S. Geological Survey National Geospatial Program LIDAR Base Specification, Version 1.2",

"ldrsens" : "Riegl Q1560 and VQ-1560i",

"ldrmaxnr" : "Unlimited",

"ldrnps" : "0.7",

"ldrdens" : "4",

"ldranps" : "0.35",

"ldradens" : "8",

"ldrfltht" : "1200",

"ldrfltsp" : "170",

"ldrscana" : "58.5",

"ldrscanr" : "107 lines per second",

"ldrpulsr" : "400",

"ldrpulsd" : "3",

"ldrpulsw" : "0.9",

"ldrwavel" : "1064",

"ldrmpia" : "1",

"ldrbmdiv" : "0.25",

"ldrswatw" : "1344",

"ldrswato" : "60",

"ldrgeoid" : "National Geodetic Survey (NGS) Geoid03",

"ldrcrs" : "NAD_1983_HARN_StatePlane_Washington_South_FIPS_4602_Feet"

},

"ldrinfo" : {

"ldrspec" : "U.S. Geological Survey National Geospatial Program LIDAR Base Specification, Version 1.2",

"ldrsens" : "Riegl Q780",

"ldrmaxnr" : "Unlimited",

"ldrnps" : "0.7",

"ldrdens" : "4",

"ldranps" : "0.35",

"ldradens" : "8",

"ldrfltht" : "1300",

"ldrfltsp" : "140",

"ldrscana" : "58.5",

"ldrscanr" : "207 lines per second",

"ldrpulsr" : "400",

"ldrpulsd" : "3",

"ldrpulsw" : "0.9",

"ldrwavel" : "1064",

"ldrmpia" : "1",

"ldrbmdiv" : "0.25",

"ldrswatw" : "1456",

"ldrswato" : "60",

"ldrgeoid" : "National Geodetic Survey (NGS) Geoid03",

"ldrcrs" : "NAD_1983_HARN_StatePlane_Washington_South_FIPS_4602_Feet"

},

"ldrinfo" : {

"ldrspec" : "U.S. Geological Survey National Geospatial Program LIDAR Base Specification, Version 1.2",

"ldrsens" : "ALS 80",

"ldrmaxnr" : "Unlimited",

"ldrnps" : "0.7",

"ldrdens" : "4",

"ldranps" : "0.35",

"ldradens" : "8",

"ldrfltht" : "1550",

"ldrfltsp" : "120",

"ldrscana" : "40",

"ldrscanr" : "48",

"ldrpulsr" : "341.6",

"ldrpulsd" : "2.5",

"ldrpulsw" : "0.9",

"ldrwavel" : "1064",

"ldrmpia" : "1",

"ldrbmdiv" : "0.22",

"ldrswatw" : "1128",

"ldrswato" : "60",

"ldrgeoid" : "National Geodetic Survey (NGS) Geoid03",

"ldrcrs" : "NAD_1983_HARN_StatePlane_Washington_South_FIPS_4602_Feet"

},

"ldrinfo" : {

"ldrspec" : "U.S. Geological Survey National Geospatial Program LIDAR Base Specification, Version 1.2",

"ldrsens" : "Riegl VQ-1560i",

"ldrmaxnr" : "Unlimited",

"ldrnps" : "0.7",

"ldrdens" : "4",

"ldranps" : "0.35",

"ldradens" : "8",

"ldrfltht" : "1650",

"ldrfltsp" : "160",

"ldrscana" : "58.5",

"ldrscanr" : "Auto",

"ldrpulsr" : "400",

"ldrpulsd" : "3",

"ldrpulsw" : "0.9",

"ldrwavel" : "1064",

"ldrmpia" : "1",

"ldrbmdiv" : "0.25",

"ldrswatw" : "1848",

"ldrswato" : "60",

"ldrgeoid" : "National Geodetic Survey (NGS) Geoid03",

"ldrcrs" : "NAD_1983_HARN_StatePlane_Washington_South_FIPS_4602_Feet"

},

"ldraccur" : {

"ldrchacc" : "0.457",

"rawnva" : "0.081",

"rawnvan" : "68",

"clsnva" : "0.086",

"clsnvan" : "68",

"clsvva" : "0.219",

"clsvvan" : "55"

},

"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" : "9",

"clasitem" : "NIR Water Surface"

},

"lasclass" : {

"clascode" : "17",

"clasitem" : "Bridge Decks"

},

"lasclass" : {

"clascode" : "20",

"clasitem" : "Ignored Ground Near Breaklines"

},

"lasclass" : {

"clascode" : "22",

"clasitem" : "Temporal Exclusion"

}

}}

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.

POSPac 8.1, RiProcess 1.8.4, RiWorld 5.1.3, SDC Import 2.2.5, Waypoint Inertial Explorer 8.7, Leica Cloudpro 1.2.4, Microstation Version 10.0, TerraScan Version 18, TerraModeler Version 18, TerraMatch Version 18, ESRI ArcGIS 10.3.1, LasMonkey 2.3.4 (Proprietary), Las Product Creator 3.1 (Proprietary), Windows 7 Operating System

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 (ACCr) of the National Standards for Spatial Data Accuracy (NSSDA) reporting standard where a theoretical point will fall within the obtained radius 95 percent of the time. Using a maximum flying height of 1,650m, this data set was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 6.8 cm RMSEx / RMSEy Horizontal Accuracy Class which equates to Positional Horizontal Accuracy = +/- 45.7 cm at a 95% confidence level.

The project specifications require that Non-Vegetated Vertical Accuracy (NVA) be computed for raw lidar point cloud swath files. The required accuracy (ACCz) is: 19.6 cm at a 95% confidence level, derived according to NSSDA, i.e., based on RMSE of 10 cm in the “bare earth” and "urban" land cover classes. The NVA was tested with 82 checkpoints located in bare earth and urban (non-vegetated) areas. These check points were not used in the calibration or post processing of the lidar point cloud data. The checkpoints were distributed throughout the project area and were surveyed using GPS techniques. See survey report for additional survey methodologies. Elevations from the unclassified lidar surface were measured for the x,y location of each check point. Elevations interpolated from the lidar surface were then compared to the elevation values of the surveyed control points. AccuracyZ has been tested to meet 19.6 cm or better Non-Vegetated Vertical Accuracy at 95% confidence level using RMSE(z) x 1.9600 as defined by the National Standards for Spatial Data Accuracy (NSSDA); assessed and reported using National Digital Elevation Program (NDEP)/ASRPS Guidelines.

For the Olympic Peninsula Area 1 survey, 82 ground check points were withheld from the calibration and post processing of the LiDAR point cloud, with resulting non-vegetated vertical accuracy of 0.337 feet (0.103 meters) as compared to unclassified LAS, and 0.271 feet (0.083 meters) as compared to the bare earth DEM, with 95% confidence.

For the Olympic Peninsula Area 1A survey, 29 quality assurance points tested 0.255 feet (0.078 meters) vertical accuracy at the 95 percent confidence level as compared to the bare earth DEM (Figure 8). As compared to the unclassified point cloud, 29 quality assurance points tested 0.276 feet (0.084 meters) vertical accuracy at the 95 percent confidence level.

For the Olympic Peninsula Area 2 survey, 331 ground check points were withheld from the calibration and post processing of the LiDAR point cloud, with resulting non-vegetated vertical accuracy of 0.266 feet (0.081 meters) as compared to unclassified LAS, and 0.282 feet (0.086 meters) as compared to the bare earth DEM, with 95% confidence.

For the Olympic Peninsula Area 3 survey, 61 ground check points were withheld from the calibration and post processing of the LiDAR point cloud, with resulting non-vegetated vertical accuracy of 0.348 feet (0.106 meters) as compared to unclassified LAS, and 0.268 feet (0.082 meters) as compared to the bare earth DEM, with 95% confidence.

LAS files include all data points collected. No points have been removed or excluded. Shaded relief images have been visually inspected for data errors such as pits, border artifacts, and shifting. Lidar flight lines have been examined to ensure consistent elevation values across overlapping flight lines. The raw point cloud is of good quality and data passes Non Vegetated Vertical Accuracy specifications.

Classified LAS files were tested by QSI for both vertical and horizontal accuracy. All data is seamless from one tile to the next, no gaps or no data areas.

Data is backed up to tape and to cloud storage.