2016 USGS Lidar DEM: West Washington

In March 2016, Quantum Spatial (QSI) was contracted by the United States Geological Survey (USGS), in collaboration with the Washington Department of Natural Resources (WADNR), to collect Light Detection and Ranging (LiDAR) data for the Western Washington 3DEP QL1 LiDAR project site in the state of Washington. The Western Washington 3DEP LiDAR project area covers approximately 3.5 million acres within portions of thirteen counties in the state of Washington.

Dataset Description: RAW flight line swaths were processed to create 13206 classified LAS 1.4 files delineated in 1/100th USGS Quadrangle tiles. Each LAS file contains LiDAR point information, which has been calibrated, controlled, and classified. Additional derived products include intensity images, hydro-flattened DEMs, highest hit surface models, and 3D breaklines of rivers and lakes within the study area.

Ground Conditions: Data was collected during the time when the least ground snow coverage was present in the area. Areas where snow was observed have been delineated in a provided snow polygon shapefile. Acquisition below aircraft free of smoke, fog and cloud cover.

The NOAA Office for Coastal Management (OCM) downloaded the WA_Western-North_2016 and WA_Western-South_2016 Digital Elevation Model (DEM) files from this USGS site: ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/Elevation/OPR/ and processed the data to the Data Access Viewer (DAV) and https.

In addition to these bare earth Digital Elevation Model (DEM) data, the lidar point data that these DEMs were created from, are also available. These data are available for custom download at the link provided in the URL section of this metadata record.

Hydro breaklines are also available. These data are available for download at the link provided in the URL section of this metadata record. Please note that these products have not been reviewed by the NOAA Office for Coastal Management (OCM) and any conclusions drawn from the analysis of this information are not the responsibility of NOAA or OCM.

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, intensity images, hydro-flattened DEMs, highest hit surface models, and 3D breaklines of rivers and lakes within the study area.

CONTRACTOR: Quantum Spatial, Inc.

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

Data acquisition was coordinated by Quantum Spatial and all Lidar data calibration, and follow-on processing were completed by Quantum Spatial.

The following are the USGS lidar fields in JSON:

{

"lidar" : {

"ldrinfo" : {

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

"ldrsens" : "Riegl LMS-Q1560 and Leica ALS80- settings below are max",

"ldrmaxnr" : "15",

"ldrnps" : "0.7 m",

"ldrdens" : "4",

"ldranps" : "0.35",

"ldradens" : "8",

"ldrfltht" : "1900m",

"ldrfltsp" : "150",

"ldrscana" : "60",

"ldrscanr" : "187",

"ldrpulsr" : "800",

"ldrpulsd" : "3",

"ldrpulsw" : "0.899",

"ldrwavel" : "1064",

"ldrmpia" : "1",

"ldrbmdiv" : "0.25",

"ldrswatw" : "2100",

"ldrswato" : "60",

"ldrcrs" : "NAD_1983_HARN_WASP_S",

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

},

"ldraccur" : {

"ldrchacc" : "0.5",

"rawnva" : "0.080 m",

"rawnvan" : "182"

},

"lasinfo" : {

"lasver" : "1.4",

"lasprf" : "6",

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

"lasolap" : "Swath overage points are identified in these files using the standard LAS Witheld and Overlap bits",

"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" : "10",

"clasitem" : "Ignored Ground Near Breakline"

},

"lasclass" : {

"clascode" : "17",

"clasitem" : "Bridge Decks"

},

"lasclass" : {

"clascode" : "21",

"clasitem" : "Temporal Snow"

},

"lasclass" : {

"clascode" : "22",

"clasitem" : "Temporal Ground"

},

"lasclass" : {

"clascode" : "23",

"clasitem" : "Temporal Default"

}

}

}}

Any conclusions drawn from the analysis of this information are not the responsibility of Quantum Spatial, Inc., USGS, WA DNR, NOAA, the Office for Coastal Management or its partners.

Data is available online for custom and bulk 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.

RiProcess v1.7.2, Applanix PosPac 7.1 SP 3, Microstation Version 8, TerraScan Version 16, TerraModeler Version 16, TerraMatch Version 16, ESRI ArcGIS 10.2, Windows 7 Operating System

The specifications require that raw Non-vegetated Vertical Accuracy (NVA) be computed from the both the raw lidar point cloud swath files and the derived DEMs. Additionally, Vegetated Vertical Accuracy (VVA) is also to be computed from the derived DEMS. The NVA was tested with 182 independent check points located in open terrain, and distributed throughout the project as feasible. These check points were not used in the calibration or post processing of the lidar point cloud data. The VVA was tested with 115 independent check points located in vegetated terrain, also witheld from the calibration and post processing of the lidar point cloud data and distributed throughout the project area as feasible. Specifications for this project require that the NVA be 0.196 meters or better AccuracyZ at the 95% confidence level and that the VVA be 29.4 cm or better AccuracyZ at the 95th percentile.

0.080 meters AccuracyZ at the 95 percent Confidence Interval for Raw LAS NVA.

0.081 meters AccuracyZ at the 95 percent Confidence Interval for DEM NVA.

The 182 independent NVA check points were surveyed using the closed level loop technique. Elevations interpolated from the unclassified lidar surface were compared to the elevation values of the surveyed NVA check points. The RMSE was computed to be 0.041 meters resulting in an AccuracyZ at the 95% confidence level of 0.080 meters. The 182 NVA check points were also compared to the elevations of the derived bare earth DEMs. The RMSE was computed to be 0.042 meters resulting in an AccuracyZ of 0.081 meters at the 95% confidence level. NVA AccuracyZ has been tested and meets the required 0.196 meter NVA at 95% confidence level using (RMSEz * 1.9600) for both the raw lidar point cloud and derived DEMs, as defined by the National Standards for Spatial Data Accuracy (NSSDA) and herein reported using National Digital Elevation Program (NDEP)/ASPRS Guidelines.

0.207 meters AccuracyZ at the 95th percentile for DEM VVA.

The 115 VVA check points were also surveyed using the closed level loop technique. Elevations for these points were compared to the elevations of the derived bare earth DEMs. The RMSE was computed to be 0.112 meters resulting in an AccuracyZ of 0.207 meters at the 95th percentile. AccuracyZ has been tested on the derived bare earth DEMs and meets the required 29.4 meter VVA using the 95th percentile of the absolute value of all vertical errors in all combined vegetation classes as defined by the National Standards for Spatial Data Accuracy (NSSDA); and herein reported using National Digital Elevation Program (NDEP)/ASPRS Guidelines.

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 Vertical Accuracy specifications.

LAS files were tested by QSI for both vertical and horizontal accuracy. All data is seamless from one tile to the next.