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      <gmd:report>
        <gmd:DQ_AbsoluteExternalPositionalAccuracy>
          <gmd:nameOfMeasure>
            <gco:CharacterString>Horizontal Positional Accuracy</gco:CharacterString>
          </gmd:nameOfMeasure>
          <gmd:evaluationMethodDescription>
            <gco:CharacterString>The horizontal accuracy of the data is better than plus or minus 1.0 m at a 95% confidence level.</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>The actual NVA accuracy was found to be RMSEz= 8.6 cm, equating to +/- 16.9 cm at 95% confidence level. The actual VVA accuracy was found to be +/- 26.8 cm at the 95th percentile.</gco:CharacterString>
          </gmd:evaluationMethodDescription>
          <gmd:result gco:nilReason="missing" />
        </gmd:DQ_AbsoluteExternalPositionalAccuracy>
      </gmd:report>
      <gmd:report>
        <gmd:DQ_QuantitativeAttributeAccuracy>
          <gmd:nameOfMeasure>
            <gco:CharacterString>Quantitation Limits</gco:CharacterString>
          </gmd:nameOfMeasure>
          <gmd:evaluationMethodDescription>
            <gco:CharacterString>Lidar vendors calibrate their lidar systems during installation of the system and then again for every project acquired.  Typical calibrations include cross flights that capture features from multiple directions that allow adjustments to be performed so that the captured features are consistent between all swaths and cross flights from all directions. Horizontal positional accuracy is achieved through rigorous processing of airborne GPS and IMU, use of control, and calibration procedures. No photo-identifiable areas could be found in the lidar intensity imagery and horizontal accuracy could not be tested for the lidar data. 
		 
		 The vertical accuracy of the lidar was tested by Dewberry with 48 independent survey checkpoints.  The survey checkpoints are evenly distributed throughout the project area and are located in areas of non-vegetated terrain, including bare earth, open terrain, and urban terrain (26), vegetated terrain, including forest, brush, tall weeds, crops, and high grass (11), and submerged bottom areas (11).  The vertical accuracy is tested by comparing survey checkpoints to a triangulated irregular network (TIN) that is created from the lidar ground and submerged bottom points.  Checkpoints are always compared to interpolated surfaces created from the lidar point cloud because it is unlikely that a survey checkpoint will be located at the location of a discrete lidar point.
		 
		 All checkpoints located in non-vegetated terrain were used to compute the Non-vegetated Vertical Accuracy (NVA).  Project specifications required a NVA of 19.6 cm at the 95% confidence level based on RMSEz (10 cm) x 1.9600.  All checkpoints located in vegetated terrain were used to compute the Vegetated Vertical Accuracy (VVA).  Project specifications required a VVA of 30.0 cm based on the 95th percentile.  All checkpoints located in bathymetric areas were used to compute an accuracy for the bathymetric data.  Project specifications required bathymetric data to meet or exceed 58.8 cm at the 95% confidence level based on RMSEz (18.5 cm) x 1.9600.</gco:CharacterString>
          </gmd:evaluationMethodDescription>
          <gmd:result gco:nilReason="missing" />
        </gmd:DQ_QuantitativeAttributeAccuracy>
      </gmd:report>
      <gmd:lineage>
        <gmd:LI_Lineage>
          <gmd:statement gco:nilReason="missing" />
          <gmd:processStep>
            <gmd:LI_ProcessStep>
              <gmd:description>
                <gco:CharacterString>Data for Marthas Vineyard and Nantucket Islands project was acquired by Leading Edge Geomatics using a Leica Chiroptera II Bathymetric and Topographic lidar sensor.  All delivered lidar data is referenced to:
				Horizontal Datum-NAD83 (2011) epoch: 2010
				Projection-UTM Zone 19 North
				Horizontal Units-meters
				Vertical Datum-NAD83
				Vertical Units-meters
				
				This dataset encompasses 7,030 500m x 500m tiles.  Both green lidar data and NIR lidar data was acquired. Leading Edge Geomatics acquired, calibrated and performed the refraction correction to the lidar data.
				
				Dewberry received the calibrated green and NIR data and verified complete coverage.  Relative accuracy of the green swaths compared to overlapping and adjacent green swaths as well as the relative accuracy of green swaths compared to overlapping and adjacent NIR swaths was verified through the use of Delta-Z (DZ) orthos created in GeoCue software.  Intraswath or within a swath relative accuracy was verified using Quick Terrain Modeler.  Profiles of elevated planar features, such as roofs, were used to verify horizontal alignment between overlapping swaths.  Dewberry then verified absolute vertical accuracy of the swath data prior to full-scale production.
				
				Dewberry used ArcGIS to create 2-D breaklines.  The bathymetric points exported by the Leica processing software were aggregated into polygons. These 2D breaklines representing the bathy areas were manually reviewed and adjusted where necessary to ensure all well-defined hydrographic features (at 1:1200-scale) were captured with breaklines.  
				
				Dewberry used algorithms in TerraScan to create the initial ground/submerged topography surface.  Dewberry used the 2-D breaklines to classify the bathymetric bottom and ground points properly in TerraScan.  All lidar data was peer-reviewed.  Dewberry's QAQC also included creating void polygons for use during review.  All necessary edits were applied to the dataset.  GeoCue software was used to update LAS header information, including all projection and coordinate reference system information.  The final lidar data are in LAS format 1.2 and point data record format 3.
				
				The final classification scheme is as follows:
				1-Unclassified
				2-Ground 
				7-Topo Noise
				9-Water
				22-Refracted Bathymetric Noise
				25-Water Column 
				26-Bathymetric Bottom or Submerged Topography
				27-Water Surface
				28-Derived Water Surface
				
				All data is then verified by an Independent QC department within Dewberry.  The independent QC is performed by separate analysts who do not perform manual classification or editing.  The independent QC involves quantitative and qualitative reviews.</gco:CharacterString>
              </gmd:description>
              <gmd:dateTime>
                <gco:DateTime>2017-01-01T00:00:00</gco:DateTime>
              </gmd:dateTime>
              <gmd:processor>
                <gmd:CI_ResponsibleParty>
                  <gmd:organisationName>
                    <gco:CharacterString>National Geodetic Survey</gco:CharacterString>
                  </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:processStep>
            <gmd:LI_ProcessStep>
              <gmd:description>
                <gco:CharacterString>The NOAA Office for Coastal Management (OCM) received files in las format. The files contained lidar elevation and intensity measurements of Marthas Vineyard and Nantucket. The data were in UTM Zone 19 coordinates and ellipsoid elevations in meters. The data classifications for the data are: 1 - unclassified, 2 - ground, 7 - topo noise, 26 - bathymetric bottom or submerged topography, 27 - water surface, 2.  OCM performed the following processing on the data for Digital Coast storage and provisioning purposes: 1. Converted from UTM Zone 19 to geographic coordinates 2. Sorted by gps time  3.  Compressed the data using laszip</gco:CharacterString>
              </gmd:description>
              <gmd:dateTime>
                <gco:DateTime>2017-02-01T00:00:00</gco:DateTime>
              </gmd:dateTime>
              <gmd:processor>
                <gmd:CI_ResponsibleParty>
                  <gmd:organisationName>
                    <gco:CharacterString>Office for Coastal Management</gco:CharacterString>
                  </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>Lidar</gco:CharacterString>
                  </gmd:title>
                  <gmd:date gco:nilReason="missing" />
                </gmd:CI_Citation>
              </gmd:sourceCitation>
            </gmd:LI_Source>
          </gmd:source>
        </gmd:LI_Lineage>
      </gmd:lineage>
    </gmd:DQ_DataQuality>
  </gmd:dataQualityInfo>
</gmi:MI_Metadata>