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This data set contains point cloud data(' in LAZ (compressed LAS) format', ''). The data may have been reprojected or otherwise modified from the original data in an automated process. Disregard projection information in this abstract and refer to the spatial reference section.
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			The custom download may be cited as National Oceanic and Atmospheric Administration (NOAA) Digital Coast Data Access Viewer.
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                processing was completed by the prime contractor. Point Cloud File Type = LAS v1.4
                Point Record Format 6, 7, 8, 9, or 10 including "File Source ID"
   The following are the USGS lidar fields in JSON:
              {
                

    "ldrinfo" : {
              

    "ldrspec" : "USGS-NGP Base Lidar Specification v1.3",

    "ldrsens" : "ALS80",

    "ldrmaxnr" : "5",

    "ldrnps" : "0.5",

    "ldrdens" : "4",

    "ldranps" : "0.35",

    "ldradens" : "8",

    "ldrfltht" : "2650",

    "ldrfltsp" : "150",

    "ldrscana" : "26.5",

    "ldrscanr" : "55",

    "ldrpulsr" : "534",

    "ldrpulsd" : "2.5",

    "ldrpulsw" : "0.75",

    "ldrwavel" : "1064",

    "ldrmpia" : "1",

    "ldrbmdiv" : "0.2",

    "ldrswatw" : "1150",

    "ldrswato" : "56",

    "ldrgeoid" : "National Geodetic Survey (NGS) GEOID12B"
  },

    "ldraccur" : {
              

    "ldrchacc" : "0.309",

    "rawnva" : "0.102",

    "rawnvan" : "107"
  },

    "lasinfo" : {
              

    "lasver" : "1.4",

    "lasprf" : "6",

    "laswheld" : "There were no withheld points identified in this project. All points
                        were used in the classification.",

    "lasolap" : "Swath "overage" points were identified in these files using the
                        standard LAS overlap bit.",

    "lasintr" : "16 bit",

    "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" : "17",

    "clasitem" : "Bridge Decks"
  },

    "lasclass" : {
              

    "clascode" : "18",

    "clasitem" : "High Noise"
  },

    "lasclass" : {
              

    "clascode" : "20",

    "clasitem" : "Ignored Ground (breakline proximity)"
  }
  }}</gco:CharacterString>
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      </gmd:MD_DataIdentification>
   </gmd:identificationInfo>
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               <gmd:version gco:nilReason="missing"/>
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                        <gco:CharacterString>Create custom data files by choosing data area, product type, map projection, file format, datum, etc. A new metadata will be produced to reflect your request using this record as a base. Change to an orthometric vertical datum is one of the many options.</gco:CharacterString>
                     </gmd:description>
                     <gmd:function>
                        <gmd:CI_OnLineFunctionCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_OnLineFunctionCode" codeListValue="download">download</gmd:CI_OnLineFunctionCode>
                     </gmd:function>
                  </gmd:CI_OnlineResource>
               </gmd:onLine>
            </gmd:MD_DigitalTransferOptions>
         </gmd:transferOptions>
         <gmd:transferOptions>
            <gmd:MD_DigitalTransferOptions>
               <gmd:onLine>
                  <gmd:CI_OnlineResource>
                     <gmd:linkage>
                        <gmd:URL>https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9895/index.html</gmd:URL>
                     </gmd:linkage>
                     <gmd:protocol>
                        <gco:CharacterString>WWW:LINK-1.0-http--link</gco:CharacterString>
                     </gmd:protocol>
                     <gmd:name>
                        <gco:CharacterString>Bulk Download</gco:CharacterString>
                     </gmd:name>
                     <gmd:description>
                        <gco:CharacterString>Bulk download of data files in LAZ format, geographic coordinates, orthometric heights. Note that the vertical datum (hence elevations) of the files here are different than described in this document. They will be in an orthometric datum.</gco:CharacterString>
                     </gmd:description>
                     <gmd:function>
                        <gmd:CI_OnLineFunctionCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_OnLineFunctionCode" codeListValue="download">download</gmd:CI_OnLineFunctionCode>
                     </gmd:function>
                  </gmd:CI_OnlineResource>
               </gmd:onLine>
            </gmd:MD_DigitalTransferOptions>
         </gmd:transferOptions>
      </gmd:MD_Distribution>
   </gmd:distributionInfo>
   <gmd:dataQualityInfo>
      <gmd:DQ_DataQuality>
         <gmd:scope>
            <gmd:DQ_Scope>
               <gmd:level>
                  <gmd:MD_ScopeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_ScopeCode" codeListValue="dataset">dataset</gmd:MD_ScopeCode>
               </gmd:level>
            </gmd:DQ_Scope>
         </gmd:scope>
         <gmd:report>
            <gmd:DQ_AbsoluteExternalPositionalAccuracy>
               <gmd:nameOfMeasure>
                  <gco:CharacterString>Horizontal Positional Accuracy</gco:CharacterString>
               </gmd:nameOfMeasure>
               <gmd:evaluationMethodDescription>
                  <gco:CharacterString>The horizontal errors in lidar data are largely a function of the Global
                    Navigation Satellite System (GNSS) positional errors, the Inertial Measurement
                    Unit (IMU) angular errors, and the flying altitude. If the accuracy of the
                    GNSS/IMU solution is known for the specific POS system, using the flying
                    altitude of the project the expected horizontal errors in the LiDAR data can be
                    estimated. Following the formula in the ASPRS Positional Accuracy Standards for
                    Digital Geospatial Data (Edition 1, Version 1.0. - November, 2014), using the
                    specifications of the POS system used and 2651 m flying altitude above ground,
                    the estimated horizontal accuracy is RMSEr = 0.34 m.</gco:CharacterString>
               </gmd:evaluationMethodDescription>
               <gmd:result gco:nilReason="missing"/>
            </gmd:DQ_AbsoluteExternalPositionalAccuracy>
         </gmd:report>
         <gmd:report>
            <gmd:DQ_AbsoluteExternalPositionalAccuracy>
               <gmd:nameOfMeasure>
                  <gco:CharacterString>Vertical Positional Accuracy</gco:CharacterString>
               </gmd:nameOfMeasure>
               <gmd:evaluationMethodDescription>
                  <gco:CharacterString>This data set was produced to meet ASPRS Positional Accuracy Standard for Digital Geospatial Data (2014) for a 10-cm RMSEz Vertical Accuracy Class.

The USGS values are as follows:
The number of Checkpoints tested for NVA : 145
The NVA RMSEz= 5.22 cm
The NVA Accuracy z at 95% confidence interval (RMSEz * 1.96) = 10.23 cm</gco:CharacterString>
               </gmd:evaluationMethodDescription>
               <gmd:result gco:nilReason="missing"/>
            </gmd:DQ_AbsoluteExternalPositionalAccuracy>
         </gmd:report>
         <gmd:report>
            <gmd:DQ_CompletenessCommission>
               <gmd:nameOfMeasure>
                  <gco:CharacterString>Completeness Report</gco:CharacterString>
               </gmd:nameOfMeasure>
               <gmd:evaluationMethodDescription>
                  <gco:CharacterString>A complete iteration of processing (GPS/IMU Processing, Raw Lidar Data Processing,
            and Verification of Coverage and Data Quality) was performed to ensure that the acquired
            data was complete, uncorrupted, and that the entire project area had been covered
            without gaps between flight lines. No void areas or missing data exist. The raw point
            cloud is of good quality and data passes Vertical Accuracy requirements. The Classified
            Point Cloud data files include all data points collected except the ones from Cross ties
            and Calibration lines. The points that have been removed or excluded are the points fall
            outside the project delivery boundary. Points are classified. A visual qualitative
            assessment was performed to ensure data completeness. No void areas or missing data
            exist. The classified point cloud is of good quality and data passes Vertical Accuracy
            requirements. The Intensity Image files cover the entire project delivery boundary. A
            visual qualitative assessment was performed to ensure data completeness. No void areas
            or missing data exist. The Intensity Image product is of good quality. The Hydro
            Breaklines cover the entire project delivery boundary and extend beyond the boundary in
            a few locations. A visual qualitative assessment was performed to ensure data
            completeness. No void areas or missing data exist. The Hydro Breakline product is of
            good quality. The DEM raster files cover the entire project delivery boundary. The
            pixels that fall outside the project delivery boundary are set to Void with a unique
            â&#x80;&#x9c;NODATAâ&#x80;&#x9d; value. The value is identified in the file headers. There are no void pixels
            inside the project boundary. A visual qualitative assessment was performed to ensure
            data completeness. No void areas or missing data exist. The bare earth surface is of
            good quality and passes Vertical Accuracy requirements.</gco:CharacterString>
               </gmd:evaluationMethodDescription>
               <gmd:result gco:nilReason="missing"/>
            </gmd:DQ_CompletenessCommission>
         </gmd:report>
         <gmd:report>
            <gmd:DQ_ConceptualConsistency>
               <gmd:nameOfMeasure>
                  <gco:CharacterString>Conceptual Consistency</gco:CharacterString>
               </gmd:nameOfMeasure>
               <gmd:evaluationMethodDescription>
                  <gco:CharacterString>Compliance with the accuracy standard was ensured by the collection of ground control
            and the establishment of GPS base stations in the project area. The following checks
            were performed: 1) The lidar data accuracy was validated by performing a full boresight
            adjustment and then checking it against the ground control prior to generating a digital
            terrain model (DTM) or other products. 2) Lidar elevation data was validated through an
            inspection of edge matching and visual inspection for quality (artifact removal). The
            following software was used for the validation: 1) RiProcess 1.8.3, RiWorld 5.0.2,
            RiAnalyze 6.2, RiServer 1.99.5; and 2) Fugro proprietary software; 20171231.</gco:CharacterString>
               </gmd:evaluationMethodDescription>
               <gmd:result gco:nilReason="missing"/>
            </gmd:DQ_ConceptualConsistency>
         </gmd:report>
         <gmd:lineage>
            <gmd:LI_Lineage>
               <gmd:statement gco:nilReason="missing"/>
               <gmd:processStep>
                  <gmd:LI_ProcessStep>
                     <gmd:description>
                        <gco:CharacterString>Once boresighting was complete for the project, the project was first set up for automatic classification. The lidar data was cut to production tiles. The low noise points, high noise points and ground points were classified automatically in this process. Fugro utilized commercial software, as well as proprietary, in-house developed software for automatic filtering. The parameters used in the process were customized for each terrain type to obtain optimum  results. Once the automated filtering was completed, the files were run through a visual inspection to ensure that the filtering was not too aggressive or not aggressive enough. In cases where the filtering was too aggressive and important terrain were filtered out, the data was either run through a different filter within local area or was corrected during the manual filtering process. Bridge deck points were classified as well during the interactive editing process.  Interactive editing was completed in visualization software that provides manual  and automatic point classification tools. Fugro utilized commercial and proprietary software for this process. All manually inspected tiles went through  a peer review to ensure proper editing and consistency. After the manual editing and peer review, all tiles went through another final automated classification routine. This process ensures only the required classifications are used in the final product (all points classified into any temporary classes during manual editing will be re-classified into the project specified classifications). Once manual inspection, QC and final autofilter is complete for the lidar tiles, the LAS data was packaged to the project specified tiling scheme, clipped to project re-projected to Albers Equal Area; NAD83 (2011), meters; NAVD88 (GEOID12B), meters. The file header was formatted to meet the project specification with File Source ID assigned. This Classified Point Cloud product was used for the generation of derived products. This product was delivered in fully compliant LAS v1.4, Point Record Format 6 with Adjusted Standard GPS Time at a precision sufficient to allow unique timestamps for each pulse. Correct and properly formatted georeference information as Open Geospatial Consortium (OGC) well known text (WKT) was assigned in all LAS file headers. Each tile has unique File Source ID assigned. The Point Source ID matches to the flight line ID in the flight trajectory files. Intensity values are included for each point, normalized to 16-bit. The following classifications are included: Class 1 Ã¢Â&#x80;Â&#x93; Processed, but unclassified; Class 2 Ã¢Â&#x80;Â&#x93; Bare earth ground; Class 7 Ã¢Â&#x80;Â&#x93; Low Noise; Class 9 Ã¢Â&#x80;Â&#x93; Water; Class 17 Ã¢Â&#x80;Â&#x93; Bridge Decks; Class 18 Ã¢Â&#x80;Â&#x93; High Noise; Class 20 - Ignored Ground (breakline proximity). The classified point cloud data was delivered in tiles without overlap using the project tiling scheme.</gco:CharacterString>
                     </gmd:description>
                     <gmd:dateTime>
                        <gco:DateTime>2020-02-10T00:00:00</gco:DateTime>
                     </gmd:dateTime>
                  </gmd:LI_ProcessStep>
               </gmd:processStep>
               <gmd:processStep>
                  <gmd:LI_ProcessStep>
                     <gmd:description>
                        <gco:CharacterString>The NOAA Office for Coastal Management (OCM) downloaded this data set from the USGS RockyWeb portal. 
The total number of files downloaded and processed was 11,503.

The data were in Albers and UTM18 (NAD83 2011), meters, and NAVD88 (Geoid12B) elevations in meters. The data were classified as: 1 - Unclassified, 2 - Ground,, 7 - Noise, 9 - Water, 17 - Bridge Decks, and 20 - Ignored Ground. OCM processed all classifications of points to the Digital Coast Data Access Viewer (DAV).

OCM performed the following processing on the data for Digital Coast storage and provisioning purposes:

1. An internal OCM script was run to check the number of points by classification and by flight ID and the gps and intensity ranges.

2. Internal OCM scripts were run on the laz files to convert from orthometric (NAVD88) elevations to ellipsoid elevations using the Geoid12B model, to convert to geographic coordinates, to assign the geokeys, to sort the data by gps time and zip the data to database and to http.</gco:CharacterString>
                     </gmd:description>
                     <gmd:dateTime>
                        <gco:DateTime>2023-11-28T00:00:00</gco:DateTime>
                     </gmd:dateTime>
                     <gmd:processor>
                        <gmd:CI_ResponsibleParty>
                           <gmd:organisationName>
                              <gmx:Anchor xlink:title="https://ror.org/05v14bq57">Office for Coastal Management</gmx:Anchor>
                           </gmd:organisationName>
                           <gmd:role>
                              <gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#gmd:CI_RoleCode" codeListValue="processor">processor</gmd:CI_RoleCode>
                           </gmd:role>
                        </gmd:CI_ResponsibleParty>
                     </gmd:processor>
                  </gmd:LI_ProcessStep>
               </gmd:processStep>
               <gmd:source>
                  <gmd:LI_Source>
                     <gmd:sourceCitation>
                        <gmd:CI_Citation>
                           <gmd:title>
                              <gco:CharacterString>Collected and Processed Lidar</gco:CharacterString>
                           </gmd:title>
                           <gmd:date gco:nilReason="missing"/>
                           <gmd:citedResponsibleParty>
                              <gmd:CI_ResponsibleParty>
                                 <gmd:organisationName>
                                    <gco:CharacterString>Fugro</gco:CharacterString>
                                 </gmd:organisationName>
                                 <gmd:role>
                                    <gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#gmd:CI_RoleCode" codeListValue="originator">originator</gmd:CI_RoleCode>
                                 </gmd:role>
                              </gmd:CI_ResponsibleParty>
                           </gmd:citedResponsibleParty>
                        </gmd:CI_Citation>
                     </gmd:sourceCitation>
                  </gmd:LI_Source>
               </gmd:source>
            <gmd:processStep><gmd:LI_ProcessStep><gmd:description><gco:CharacterString>
                            The dataset has been mosaiced, reprojected, and clipped as needed from the original input files using PDAL and GDAL commands.
                        </gco:CharacterString></gmd:description><gmd:dateTime><gco:DateTime>2026-07-02</gco:DateTime></gmd:dateTime><gmd:processor><gmd:CI_ResponsibleParty><gmd:individualName><gco:CharacterString>NOAA Office for Coastal Management</gco:CharacterString></gmd:individualName><gmd:contactInfo><gmd:CI_Contact><gmd:address><gmd:CI_Address><gmd:electronicMailAddress><gco:CharacterString>coastal.info@noaa.gov</gco:CharacterString></gmd:electronicMailAddress></gmd:CI_Address></gmd:address></gmd:CI_Contact></gmd:contactInfo><gmd:role><gmd:CI_RoleCode codeList="https://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#gmd:CI_RoleCode" codeListValue="processor">processor</gmd:CI_RoleCode></gmd:role></gmd:CI_ResponsibleParty></gmd:processor></gmd:LI_ProcessStep></gmd:processStep></gmd:LI_Lineage>
         </gmd:lineage>
      </gmd:DQ_DataQuality>
   </gmd:dataQualityInfo>
</gmi:MI_Metadata>