<?xml version="1.0" encoding="UTF-8"?>
<metadata>
	<idinfo>
		<citation>
			<citeinfo>
				<origin>NV5 Geospatial</origin>
				<pubdate>20240322</pubdate>
				<title>Task Name:CA North Sierra 11 Contract: 140G0221D0012, Task Order: 140G0222F0176</title>
				<geoform>Raster Digital Data</geoform>
			</citeinfo>
		</citation>
		<descript>
			<abstract>Product: CA North Sierra 11 2022 Intensity Imagery.
				Geographic Extent: This dataset and derived products encompass an area covering approximately 1,771 acres of Sierra Nevada Central region.
				Dataset Description: Lidar flight line swaths were processed to create 4,721 classified LAS 1.4 files delineated in 1,000m x 1,000m tiles. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. All first returns of valid/non noise classes were were used to create 4,721 0.5 meter intensity images delineated in 1,000m x 1,000m tiles. Additional derived products include classified LAS, hydro-flattened DEMs, highest hit surface models, and 3D breaklines of rivers and lakes within the study area. Ground Conditions: Acquisition occurred free of smoke, fog and cloud cover.</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 3D Elevation Program and the CA North Sierra 11 2022 contract. The lidar point cloud data were used to create classified lidar LAS files, intensity images, interpolated DEMs, hydro-flattened DEMs, highest hit surface models, and 3D breaklines of rivers and lakes within the study area.</purpose>
			<supplinf>USGS Contract No. 140G0221D0012
				Raster File Type = TIFF
				Bit Depth/Pixel Type = 8 bit
				Raster Cell Size = 0.5
				Intensity Values Normalized To = 16 bit
			</supplinf>
		</descript>
		<timeperd>
			<timeinfo>
				<rngdates>
					<begdate>20220602</begdate>
					<enddate>20220825</enddate>
				</rngdates>
			</timeinfo>
			<current>ground condition</current>
		</timeperd>
		<status>
			<progress>Complete</progress>
			<update>As needed</update>
		</status>
		<spdom>
			<bounding>
				<westbc>-120.060684</westbc>
				<eastbc>-119.322758</eastbc>
				<northbc>38.221184</northbc>
				<southbc>36.868443</southbc>
			</bounding>
			<lboundng>
				<leftbc>232000.000000</leftbc>
				<rightbc>293000.000000</rightbc>
				<topbc>4233000.000000</topbc>
				<bottombc>4084499.367500</bottombc>
			</lboundng>
		</spdom>
		<keywords>
			<theme>
				<themekt>none</themekt>
				<themekey>Raster</themekey>
				<themekey>Intensity</themekey>
				<themekey>remote sensing</themekey>
				<themekey>Lidar</themekey>
			</theme>
			<place>
				<placekt>none</placekt>
				<placekey>California</placekey>
			</place>
		</keywords>
		<accconst>These data are considered provisional as they have not yet been reviewed by client or designated agency.</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>Data covers the entire area specified for the project</logic>
		<complete>A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist.</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 18 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>CA North Sierra 11 2022 Ground Control</srcused>
				<procdate>20240322</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 final NVA and VVA values for the project using ground control quality check points. Final density information will also be calculated.</procdesc>
				<procdate>20240322</procdate>
			</procstep>
			<procstep>
				<procdesc>Intensity Image creation: Intensity images were created for each tile from all valid first returns as 8 bit TIFFs using NV5 Geospatial and ArcGIS software.</procdesc>
				<procdate>20240322</procdate>
			</procstep>
		</lineage>
	</dataqual>
	<spdoinfo>
		<direct>Raster</direct>
		<rastinfo>
			<rasttype>Pixel</rasttype>
			<rowcount>2,000</rowcount>
			<colcount>2,000</colcount>
		</rastinfo>
	</spdoinfo>
	<spref>
		<horizsys>
			<planar>
				<gridsys>
					<gridsysn>Universal Transverse Mercator</gridsysn>
					<utm>
						<utmzone>11</utmzone>
						<transmer>
							<sfctrmer>0.99960000</sfctrmer>
							<longcm>-117.00000000</longcm>
							<latprjo>0.00000000</latprjo>
							<feast>500000.00000000</feast>
							<fnorth>0.00000000</fnorth>
						</transmer>
					</utm>
				</gridsys>
				<planci>
					<plance>row and column</plance>
					<coordrep>
						<absres>0.5</absres>
						<ordres>0.5</ordres>
					</coordrep>
					<plandu>Meters</plandu>
				</planci>
			</planar>
			<geodetic>
				<horizdn>North American Datum of 1983 2011</horizdn>
				<ellips>GRS_1980</ellips>
				<semiaxis>6378137.0</semiaxis>
				<denflat>298.257222101</denflat>
			</geodetic>
		</horizsys>
	</spref>
	<metainfo>
		<metd>20240322</metd>
		<metrd>20240322</metrd>
		<metc>
			<cntinfo>
				<cntorgp>
					<cntorg>NV5 Geospatial</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>