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                  <gco:CharacterString>LiDAR flight lines have been examined to ensure that there was at least 55 - 75% sidelap, there are no gaps between flight lines, and overlapping flight lines have consistent elevation values. Shaded relief images have been visually inspected for data errors such as pits, border artifacts, gaps, and shifting.  The data were examined at a 1:3000 scale.</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>Acquisition. 
				LiDAR data acquisition was conducted from 20170614 to 20170709. The survey utilized a Leica ALS80 sensor mounted in a Cessna Caravan. Near nadir scan angles were used to increase penetration of vegetation to ground surfaces. Ground level GPS and aircraft IMU were collected during the flight.</gco:CharacterString>
                     </gmd:description>
                     <gmd:dateTime>
                        <gco:DateTime>2017-07-10T00:00:00</gco:DateTime>
                     </gmd:dateTime>
                  </gmd:LI_ProcessStep>
               </gmd:processStep>
               <gmd:processStep>
                  <gmd:LI_ProcessStep>
                     <gmd:description>
                        <gco:CharacterString>Processing.
        1. TRAJECTORY:  Aircraft trajectory (position and attitude) were calculated based on on-board GPS and IMU data with post-processing refinement through coincident static GPS collection.          
        2. POST-PROCESSING:  Laser point return coordinates (x,y,z) were computed using sensor-specific post processing software, combining LiDAR return range and intensity information with aircraft trajectory information.
        3. INITIAL QAQC:  The post-processed LiDAR files were assembled into flight lines and reviewed for gaps and consistency, as well as systematic noise.
        4. CALIBRATION:  Custom algorithms evaluated individual swaths for misalignments based on IMU configuration as well as aircraft attitude variability.  Offsets were resolved through surface and linear matching algorithms that minimize variability in elevation and slope. Descriptive statistics, thresholds, and specifications providing transparency for data calibration are discussed in the accompanying Data Report.
        5. GROUND MODELING:  Ground classified point cloud was generated through proprietary data processing tools, with settings and thresholds appropriate to landscape and vegetation condition.
		6. ARTIFACT FILTRATION:  Noise and processing artifacts were filtered using post-processing software and proprietary quality control methods.
        7. ACCURACY ASSESSMENT:  Vertical accuracy for the LiDAR dataset was assessed against reserved Quality Assurance Points (QAPs) distributed throughout the study area and not used during calibration processes. See the accompanying Data Report for methodology, descriptive statistics, and relevant standards and reporting language.
        8. DATA PRODUCT:  LiDAR points classified as 'ground' were output as a digital elevation model (DEM).
		9. Hydro Flattening Breakline Processing: 
		Class 2 LiDAR was used to create a bare earth surface model.  E-Cognition utilized rasters created within Bentley Microstation to auto-generate breaklines of inland streams and rivers with a 100 foot nominal width and Inland Ponds of 2 acres or greater surface area. Breaklines for Lakes with surface area greater than 2 acres were generated using heads-up digitization.
		Elevation values were assigned to all Inland Ponds and Lakes within ESRI ArcMap; Inland Pond and Lake Islands, Inland Stream and River Islands were assigned elevation values from within ESRI ArcMap.
		All ground (ASPRS Class 2) LiDAR data inside of the collected inland breaklines were then classified to water (ASPRS Class 9) using TerraScan macro functionality.  A buffer of 2.1 meter was also used around each hydro-flattened stream.  These points were moved from ground (ASPRS Class 2) to Ignored Ground (ASPRS Class 10).
		The breakline files were then translated to ESRI File-Geodatabase format using ESRI conversion tools.</gco:CharacterString>
                     </gmd:description>
                     <gmd:dateTime>
                        <gco:DateTime>2017-07-10T00:00:00</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) received 5472 hydro-flattened bare earth DEM files in Arc Grid format from DOGAMI. The data were in UTM Zone 11, NAD83 (2011), meters, coordinates and NAVD88 (Geoid12B) elevations in meters. The EPSG codes (Horizontal - 6340, Vertical - 5703), were assigned. The data were converted to GeoTIFF format for ingest into the Digital Coast Data Access Viewer and to adhere to the Open Data Policy.</gco:CharacterString>
                     </gmd:description>
                     <gmd:dateTime>
                        <gco:DateTime>2019-11-13T00:00:00</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:LI_Lineage>
         </gmd:lineage>
      </gmd:DQ_DataQuality>
   </gmd:dataQualityInfo>
</gmi:MI_Metadata>
