<?xml version="1.0" encoding="UTF-8"?>
<metadata>
	<idinfo>
		<citation>
			<citeinfo>
				<origin>Quantum Spatial, Inc.</origin>
				<pubdate>20190810</pubdate>
				<title>Task Name: WA Olympic Peninsula LiDAR 2017 B17, USGS Contract: G16PC00016, Task Order: G17PD00827</title>
				<geoform>Raster Digital Data</geoform>
			</citeinfo>
		</citation>
		<descript>
			<abstract>
			Geographic Extent: This dataset and derived products encompass Olympic Peninsula Area 2, an approximately 1,547 square mile portion of the Olympic Peninsula 3DEP project area, which covers approximately 5,352 square miles of Western Washington in the Olympic Peninsula region. 
			Dataset Description: RAW flight line swaths were processed to create 3,371 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, lakes, coastlines and bridges within the study area. Tiled deliverables that are split between delivery boundaries have been given an extension of "_[delivery#]" at the end of the file name. For this delivery, tiled deliverables have been given an "_2" extension. 
			Ground Conditions: Acquisition below aircraft free of smoke, fog and cloud cover. Ground Control Points were acquired and calibrated by Quantum Spatial, Inc.
			Partial Lens Obstruction Issue: During calibration it was noticed that missions 20180210_SN750_F1 and 20180212_SN750_F1 exhibited degraded returns in the second channel. After review, it was determined that the most likely cause was a physical obstruction in front on the lens such as exhaust particulates or condensation. This obstruction resulted in lower-strength returns on the port side of the channel, which manifested as points with artificially low intensity values, or in extreme cases, no points recorded at the farthest scan angle/range. Further assessment concluded affected areas were covered by channel one as well as overlapping opposing flightlines, thus these missions would be accepted and processed. In order to improve the intensity images of these flights, TerraScan’s “Smoothen Points” tool was used to borrow intensity values from spatially related points in channel one.
			</abstract>
			<purpose>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.</purpose>
			<supplinf>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.
				Raster File Type = TIFF
				Bit Depth/Pixel Type = 8-bit
				Raster Cell Size = 3 foot
				Intensity Values Normalized To = 16-bit
			</supplinf>
		</descript>
		<timeperd>
			<timeinfo>
				<rngdates>
					<begdate>20180219</begdate>
					<enddate>20190425</enddate>
				</rngdates>
			</timeinfo>
			<current>ground condition</current>
		</timeperd>
		<status>
			<progress>Complete</progress>
			<update>None Planned</update>
		</status>
		<spdom>
			<bounding>
				<westbc>-124.165360</westbc>
				<eastbc>-123.019618</eastbc>
				<northbc>46.991462</northbc>
				<southbc>46.118543</southbc>
			</bounding>
			<lboundng>
				<leftbc>725542.297654</leftbc>
				<rightbc>1001924.230949</rightbc>
				<topbc>615029.021279</topbc>
				<bottombc>307270.921794</bottombc>
			</lboundng>
		</spdom>
		<keywords>
			<theme>
				<themekt>none</themekt>
				<themekey>LAS Point Cloud</themekey>
				<themekey>remote sensing</themekey>
				<themekey>Intensity Image</themekey>
				<themekey>lidar</themekey>
			</theme>
			<place>
				<placekt>none</placekt>
				<placekey>Washington</placekey>
				<placekey>Olympic Peninsula</placekey>
				<placekey>Pacific County</placekey>
				<placekey>Lewis County</placekey>
				<placekey>Wahkiakum County</placekey>
				<placekey>Grays Harbor County</placekey>
			</place>
		</keywords>
		<accconst>No restrictions apply to these data.</accconst>
		<useconst>None. However, users should be aware that temporal changes may have occurred since this dataset was collected and that some parts of these data may no longer represent actual surface conditions. Users should not use these data for critical applications without a full awareness of its limitations. Acknowledgment of the U.S. Geological Survey would be appreciated for products derived from these data.</useconst>
	</idinfo>
	<dataqual>
		<logic>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.</logic>
		<complete>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.</complete>
		<lineage>
			<procstep>
				<procdesc>LiDAR Pre-Processing:
					1. Review flight lines and data to ensure complete coverage of the study area and positional accuracy of the laser points.
					2. Resolve kinematic corrections for aircraft position data using kinematic aircraft GPS and static ground GPS data.
					3. Develop a smoothed best estimate of trajectory (SBET) file that blends post-processed aircraft position with sensor head position and attitude recorded throughout the survey.
					4. Calculate laser point position by associating SBET position to each laser point return time, scan angle, intensity, etc. Create raw laser point cloud data for the entire survey in *.las format. Convert data to orthometric elevations by applying a geoid correction.
					5. Import raw laser points into manageable blocks to perform manual relative accuracy calibration and filter erroneous points. Classify ground points for individual flight lines.
					6. Using ground classified points per each flight line, test the relative accuracy. Perform automated line-to-line calibrations for system attitude parameters (pitch, roll, heading), mirror flex (scale) and GPS/IMU drift. Calculate calibrations on ground classified points from paired flight lines and apply results to all points in a flight line. Use every flight line for relative accuracy calibration.
					7. Adjust the point cloud by comparing ground classified points to supplemental ground control points.</procdesc>
				<srcused>Base_Station_Control, SBETs, SGCPs, RAW_LiDAR</srcused>
				<procdate>20190425</procdate>
			</procstep>
			<procstep>
				<procdesc>LiDAR Post-Processing:
					1. Classify data to ground and other client designated classifications using proprietary classification algorithms.
					2. Manually QC data classification
					3. After completion of classification and final QC approval, calculate NVA and VVA, and density information for the project.</procdesc>
				<procdate>20190425</procdate>
			</procstep>
			<procstep>
				<procdesc>Intensity Image creation: Intensity images were created for each tile from all valid first returns as 8-bit TIFFs using proprietary Quantum Spatial software.</procdesc>
				<srcused>Classified_LiDAR</srcused>
				<procdate>20190425</procdate>
			</procstep>
		</lineage>
	</dataqual>
	<spdoinfo>
		<direct>Raster</direct>
		<rastinfo>
			<rasttype>Pixel</rasttype>
		</rastinfo>
	</spdoinfo>
	<spref>
		<horizsys>
			<planar>
				<gridsys>
					<gridsysn>State Plane Coordinate System 1983</gridsysn>
					<spcs>
						<spcszone>4602</spcszone>
						<lambertc>
							<stdparll>45.83333333</stdparll>
							<stdparll>47.33333333</stdparll>
							<longcm>-120.5</longcm>
							<latprjo>45.33333333</latprjo>
							<feast>1640416.667</feast>
							<fnorth>0</fnorth>
						</lambertc>
					</spcs>
				</gridsys>
				<planci>
					<plance>coordinate pair</plance>
					<coordrep>
						<absres>3</absres>
						<ordres>3</ordres>
					</coordrep>
					<plandu>U.S. Survey Feet</plandu>
				</planci>
			</planar>
			<geodetic>
				<horizdn>North American Datum of 1983 (CORS96) defined (HARN)</horizdn>
				<ellips>GRS_1980</ellips>
				<semiaxis>6378137.0</semiaxis>
				<denflat>298.257223563</denflat>
			</geodetic>
		</horizsys>
	</spref>
	<metainfo>
		<metd>20190810</metd>
		<metrd>20190810</metrd>
		<metc>
			<cntinfo>
				<cntorgp>
					<cntorg>Quantum Spatial, Inc.</cntorg>
				</cntorgp>
				<cntaddr>
					<addrtype>mailing and physical</addrtype>
					<address>1100 NE Circle Blvd., Suite 126</address>
					<city>Corvallis</city>
					<state>OR</state>
					<postal>97330</postal>
					<country>USA</country>
				</cntaddr>
				<cntvoice>541-752-1204</cntvoice>
			</cntinfo>
		</metc>
		<metstdn>FGDC Content Standard for Digital Geospatial Metadata</metstdn>
		<metstdv>FGDC-STD-001-1998</metstdv>
		<metac>None</metac>
		<metuc>None</metuc>
		<metsi>
			<metscs>None</metscs>
			<metsc>Unclassified</metsc>
			<metshd>None</metshd>
		</metsi>
		<metextns>
			<onlink>None</onlink>
			<metprof>None</metprof>
		</metextns>
	</metainfo>
</metadata>