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            <gco:CharacterString>Original Dataset Geographic Extent: This dataset and derived products encompass an area covering approximately 1,021,407 acres of Southern California. 

Original Dataset Description: RAW flight line swaths were processed to create 4,438 classified LAS 1.4 files delineated in 1,000 m x 1,000 m 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: Acquisition below aircraft 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 GeoTIFF files hosted by USGS on Amazon Web Services.


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                              xlink:title="Universal (CC0 1.0) Public Domain Dedication"
                              xlink:href="https://creativecommons.org/publicdomain/zero/1.0/">To the extent possible under law, the U.S. Government has waived all copyright and related or neighboring rights to this dataset.</gmx:Anchor>
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         <gmd:resourceConstraints>
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               <gmd:accessConstraints>
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                  </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>Vertical Positional Accuracy</gco:CharacterString>
               </gmd:nameOfMeasure>
               <gmd:evaluationMethodDescription>
                  <gco:CharacterString>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 80 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 61 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.

The 80 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 0.052 meters resulting in an AccuracyZ at the 95% confidence level of 0.102 meters. The 80 NVA check points were also compared to the elevations of the derived bare earth DEMs. The RMSE was computed to be 0.058 meters resulting in an AccuracyZ of 0.113 meters at the 95% confidence level. NVA AccuracyZ has been tested and meets the required 19.6 cm 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.	

The 61 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 0.66 meters resulting in an AccuracyZ of 0.127 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.</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>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.</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>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.</gco:CharacterString>
               </gmd:evaluationMethodDescription>
               <gmd:result gco:nilReason="missing"/>
            </gmd:DQ_ConceptualConsistency>
         </gmd:report>
         <gmd:lineage>
            <gmd:LI_Lineage>
               <gmd:statement>
                  <gco:CharacterString>The NOAA Office for Coastal Management (OCM) ingested references to the USGS GeoTIFF files that are hosted on Amazon Web Services (AWS), into the Digital Coast Data Access Viewer (DAV). The DAV accesses the raster data as it resides on AWS.</gco:CharacterString>
               </gmd:statement>
               <gmd:processStep>
                  <gmd:LI_ProcessStep>
                     <gmd:description>
                        <gco:CharacterString>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 geoid12b correction.
				5. Import raw laser points into manageable blocks (less than 500 MB) 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>2017-10-19T00:00:00</gco:DateTime>
                     </gmd:dateTime>
                  </gmd:LI_ProcessStep>
               </gmd:processStep>
               <gmd:processStep>
                  <gmd:LI_ProcessStep>
                     <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 NVA for the project using ground control quality check points.</gco:CharacterString>
                     </gmd:description>
                     <gmd:dateTime>
                        <gco:DateTime>2017-10-19T00:00:00</gco:DateTime>
                     </gmd:dateTime>
                  </gmd:LI_ProcessStep>
               </gmd:processStep>
               <gmd:processStep>
                  <gmd:LI_ProcessStep>
                     <gmd:description>
                        <gco:CharacterString>Hydroflattening Breaklines and Hydroflattened DEM creation: Water boundary polygons were developed using an algorithm which weights LiDAR-derived slopes, intensities, and return densities to detect the water's edge. The water's edge was then manually reviewed and edited as necessary. Elevations were assigned to the water's edge through neighborhood statistics identifying the lowest LiDAR return from the water surface. Lakes were assigned a consistent elevation for an entire polygon while rivers were assigned consistent elevations on opposing banks and smoothed to ensure downstream flow through the entire river channel. These breaklines were incorporated into the hydro-flattened DEM by enforcing triangle edges (adjacent to the breakline) to the elevation values derived from the breakline. This implementation corrected interpolation along the hard edge. Breaklines were also used to classify all ground points within the identified water bodies to class 9 (water).</gco:CharacterString>
                     </gmd:description>
                  </gmd:LI_ProcessStep>
               </gmd:processStep>
               <gmd:processStep>
                  <gmd:LI_ProcessStep>
                     <gmd:description>
                        <gco:CharacterString>The NOAA Office for Coastal Management (OCM) created references to the USGS GeoTIFF files that were ingested into the NOAA Digital Coast Data Access Viewer (DAV). No changes were made to the data. The DAV will access the raster data as it resides on Amazon Web Services (AWS).

These are the GeoTIFF files that are being accessed:
https://prd-tnm.s3.amazonaws.com/index.html?prefix=StagedProducts/Elevation/OPR/Projects/CA_SE_Fault_Zone_Lidar_2017_D17/CA_SE_Fault_Zone_2017/TIFF/
</gco:CharacterString>
                     </gmd:description>
                     <gmd:dateTime>
                        <gco:DateTime>2026-06-02T00:00:00</gco:DateTime>
                     </gmd:dateTime>
                     <gmd:processor>
                        <gmd:CI_ResponsibleParty>
                           <gmd:organisationName>
                              <gco:CharacterString>NOAA Office for Coastal Management</gco:CharacterString>
                           </gmd:organisationName>
                           <gmd:contactInfo>
                              <gmd:CI_Contact>
                                 <gmd:phone>
                                    <gmd:CI_Telephone>
                                       <gmd:voice>
                                          <gco:CharacterString>(843) 740-1202</gco:CharacterString>
                                       </gmd:voice>
                                    </gmd:CI_Telephone>
                                 </gmd:phone>
                                 <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="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>USGS AWS GeoTIFF Files - CA_SE_Fault_Zone_2017</gco:CharacterString>
                           </gmd:title>
                           <gmd:date gco:nilReason="missing"/>
                           <gmd:citedResponsibleParty>
                              <gmd:CI_ResponsibleParty>
                                 <gmd:organisationName>
                                    <gco:CharacterString>USGS</gco:CharacterString>
                                 </gmd:organisationName>
                                 <gmd:contactInfo>
                                    <gmd:CI_Contact>
                                       <gmd:onlineResource>
                                          <gmd:CI_OnlineResource>
                                             <gmd:linkage>
                                                <gmd:URL>https://prd-tnm.s3.amazonaws.com/index.html?prefix=StagedProducts/Elevation/OPR/Projects/CA_SE_Fault_Zone_Lidar_2017_D17/CA_SE_Fault_Zone_2017/TIFF/</gmd:URL>
                                             </gmd:linkage>
                                             <gmd:protocol>
                                                <gco:CharacterString>WWW:LINK-1.0-http--link</gco:CharacterString>
                                             </gmd:protocol>
                                             <gmd:name>
                                                <gco:CharacterString>USGS AWS GeoTIFF Files for CA_SE_Fault_Zone_2017</gco:CharacterString>
                                             </gmd:name>
                                             <gmd:description>
                                                <gco:CharacterString>Source Citation URL</gco:CharacterString>
                                             </gmd:description>
                                             <gmd:function>
                                                <gmd:CI_OnLineFunctionCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_OnLineFunctionCode"
                                                                           codeListValue="information">information</gmd:CI_OnLineFunctionCode>
                                             </gmd:function>
                                          </gmd:CI_OnlineResource>
                                       </gmd:onlineResource>
                                    </gmd:CI_Contact>
                                 </gmd:contactInfo>
                                 <gmd:role>
                                    <gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#gmd:CI_RoleCode"
                                                     codeListValue="publisher">publisher</gmd:CI_RoleCode>
                                 </gmd:role>
                              </gmd:CI_ResponsibleParty>
                           </gmd:citedResponsibleParty>
                        </gmd:CI_Citation>
                     </gmd:sourceCitation>
                  </gmd:LI_Source>
               </gmd:source>
            </gmd:LI_Lineage>
         </gmd:lineage>
      </gmd:DQ_DataQuality>
   </gmd:dataQualityInfo>
   <gmi:acquisitionInformation>
      <gmi:MI_AcquisitionInformation>
         <gmi:instrument>
            <gmi:MI_Instrument>
               <gmi:identifier>
                  <gmd:MD_Identifier>
                     <gmd:code>
                        <gco:CharacterString>Leica ALS80</gco:CharacterString>
                     </gmd:code>
                  </gmd:MD_Identifier>
               </gmi:identifier>
               <gmi:type>
                  <gco:CharacterString>Lidar</gco:CharacterString>
               </gmi:type>
               <gmi:description>
                  <gco:CharacterString/>
               </gmi:description>
            </gmi:MI_Instrument>
         </gmi:instrument>
      </gmi:MI_AcquisitionInformation>
   </gmi:acquisitionInformation>
</gmi:MI_Metadata>
