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Geographic Extent: This dataset and derived products encompass an area covering approximately 894,095 acres on the western coast of Alaska along Norton Sound. 
AK_TyphoonMerbokNV5_1 - covers approximately 685,389 acres on the western coast of Alaska along Norton Sound
AK_TyphoonMerbokNV5_2 - covers approximately 208,706 acres on the western coast of Alaska along Norton Sound

Original Dataset Description: The Typhoon Merbok Alaska Topographic Lidar 2024 project called for the planning, acquisition, and processing of lidar data collected to Quality Level 1 (QL1) standards. Project specifications are based on the U.S. Geological Survey National Geospatial Program Lidar Base Specification Version 2023, Revision A. Lidar data was delivered as calibrated and classified LAS 1.4 files. Non-Vegetated Vertical Accuracy (NVA) was assessed using check points located on bare earth in clear, unobstructed areas. Vegetated Vertical Accuracy (VVA) was assessed using check points in Tall grass, Shrub landcover types. Single swath nominal pulse spacing (NPS) was designed to be 0.35 meters at nadir. Aggregate Nominal Pulse Spacing (ANPS) was calculated to be 0.30 meters using all valid first return points. Derived products include: Intensity Imagery, Hydro-flattened Bare Earth Digital Elevation Models (DEMs), maximum surface height rasters (DSMs), swath separation RGB images, and 3D waters edge breaklines.

Ground Conditions: Ground condition was free of snow and acquisition occurred free of smoke, fog and cloud cover.

This metadata record supports the data entry in the NOAA Digital Coast Data Access Viewer (DAV). For this data set, the DAV is leveraging the Entwine Point Tiles (EPT) hosted by USGS on Amazon Web Services.

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&lt;ldrpulsr&gt;2000&lt;/ldrpulsr&gt;
&lt;ldrpulsd&gt;3&lt;/ldrpulsd&gt;
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&lt;ldrwavel&gt;1064&lt;/ldrwavel&gt;
&lt;ldrmpia&gt;1&lt;/ldrmpia&gt;
&lt;ldrbmdiv&gt;0.23&lt;/ldrbmdiv&gt;
&lt;ldrswatw&gt;1792&lt;/ldrswatw&gt;
&lt;ldrswato&gt;23&lt;/ldrswato&gt;
&lt;ldrgeoid&gt;GEOID 12B&lt;/ldrgeoid&gt;
&lt;/ldrinfo&gt;
&lt;ldrinfo&gt;
&lt;ldrspec&gt;U.S. Geological Survey National Geospatial Program Lidar Base Specification Version 2023, Revision A&lt;/ldrspec&gt;
&lt;ldrsens&gt;Riegl VQ-1560ii-S&lt;/ldrsens&gt;
&lt;ldrmaxnr&gt;5&lt;/ldrmaxnr&gt;
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&lt;ldrdens&gt;8&lt;/ldrdens&gt;
&lt;ldranps&gt;0.30&lt;/ldranps&gt;
&lt;ldradens&gt;11.47&lt;/ldradens&gt;
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&lt;ldrfltsp&gt;160&lt;/ldrfltsp&gt;
&lt;ldrscana&gt;58.5&lt;/ldrscana&gt;
&lt;ldrscanr&gt;320&lt;/ldrscanr&gt;
&lt;ldrpulsr&gt;1350&lt;/ldrpulsr&gt;
&lt;ldrpulsd&gt;3&lt;/ldrpulsd&gt;
&lt;ldrpulsw&gt;0.46&lt;/ldrpulsw&gt;
&lt;ldrwavel&gt;1064&lt;/ldrwavel&gt;
&lt;ldrmpia&gt;1&lt;/ldrmpia&gt;
&lt;ldrbmdiv&gt;0.23&lt;/ldrbmdiv&gt;
&lt;ldrswatw&gt;2258&lt;/ldrswatw&gt;
&lt;ldrswato&gt;23&lt;/ldrswato&gt;
&lt;ldrgeoid&gt;GEOID 12B&lt;/ldrgeoid&gt;
&lt;/ldrinfo&gt;
&lt;ldraccur&gt;
&lt;ldrchacc&gt;0&lt;/ldrchacc&gt;
&lt;rawnva&gt;0&lt;/rawnva&gt;
&lt;rawnvan&gt;0&lt;/rawnvan&gt;
&lt;/ldraccur&gt;
&lt;lasinfo&gt;
&lt;lasver&gt;1.4&lt;/lasver&gt;
&lt;lasprf&gt;6&lt;/lasprf&gt;
&lt;laswheld&gt;Withheld (ignore) points are identified in these files using the standard LAS Withheld bit.&lt;/laswheld&gt;
&lt;lasolap&gt;The overlap bit was not used to identify any points in the lidar point cloud.&lt;/lasolap&gt;
&lt;lasintr&gt;16&lt;/lasintr&gt;
&lt;lasclass&gt;
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&lt;lasclass&gt;
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Accuracy (NSSDA) reporting standard where a theoretical point will fall within the obtained radius 95 percent of the time.

AK_TyphoonMerbokNV5_1 (Work Unit 300810)
Based on a flying altitude of 2016 meters, an IMU error of 0.003 decimal degrees, and a GNSS positional error of 0.023 meters, this project was produced to meet 0.329 meters horizontal accuracy at the 95% confidence level.

AK_TyphoonMerbokNV5_2 (Work Unit 301214)
Based on a flying altitude of 2016 meters, an IMU error of 0.002 decimal degrees, and a GNSS positional error of 0.023 meters, this project was produced to meet 0.222 meters horizontal accuracy at the 95% confidence level.</gco:CharacterString>
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USGS Determined Vertical Accuracy
Non-Vegetated Vertical Accuracy (NVA) = 2.73 cm RMSE
Vegetated Vertical Accuracy (VVA) = 20.20 cm at the 95th Percentile

Refer to the USGS Project Report. A link to this report is provided in the URL section of this metadata record.</gco:CharacterString>
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               <gmd:result gco:nilReason="missing"/>
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               <gmd:evaluationMethodDescription>
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               <gmd:result gco:nilReason="missing"/>
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         <gmd:lineage>
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               <gmd:processStep>
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				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 12B 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.</gco:CharacterString>
                     </gmd:description>
                     <gmd:dateTime>
                        <gco:DateTime>2025-03-26T00:00:00</gco:DateTime>
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               <gmd:processStep>
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                     <gmd:description>
                        <gco:CharacterString>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, VVA, and density information for the project using ground control quality check points.</gco:CharacterString>
                     </gmd:description>
                     <gmd:dateTime>
                        <gco:DateTime>2025-03-26T00:00:00</gco:DateTime>
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               </gmd:processStep>
               <gmd:processStep>
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                     <gmd:description>
                        <gco:CharacterString>Original point clouds in LAS/LAZ format were restructured as Entwine Point Tiles and stored on Amazon Web Services. The data were re-projected horizontally to WGS84 web mercator (EPSG 3857) and the vertical units of NAVD88 (Geoid12B), meters were retained.</gco:CharacterString>
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                        <gco:CharacterString>The NOAA Office for Coastal Management (OCM) created references to the Entwine Point Tiles (EPT) that were ingested into the NOAA Digital Coast Data Access Viewer (DAV). No changes were made to the data. The DAV will access the point cloud as it resides on Amazon Web Services (AWS) under the usgs-lidar-public container.

These are the AWS URLs being accessed:
https://s3-us-west-2.amazonaws.com/usgs-lidar-public/AK_TyphoonMerbokNV5_1_F23/ept.json
https://s3-us-west-2.amazonaws.com/usgs-lidar-public/AK_TyphoonMerbokNV5_2_F23/ept.json
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