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            <gco:CharacterString>Morro Bay 2022 Topobathymetric Lidar project data were collected by NV5 Geospatial (NV5) using a Riegl VQ880GII system. Morro Bay 2022 acquisition occurred on 20220614 in two missions. The Morro Bay 2022 dataset includes topobathymetric lidar data in a LAS format 1.4, point data record format 6, with the following classifications in accordance with project specifications and the American Society for Photogrammetry and Remote Sensing (ASPRS) classification standards with the topobathymetric lidar domain profile:
			1   - unclassified
			1O  - edge clip
			2   - ground
			7W  - low noise
			9   - NIR water surface
			18W - high noise
			40  - bathymetric bottom or submerged topography
			41  - Green water surface
                        43  - Submerged object, not otherwise specified (For Morro Bay, oyster reefs have this classification, 
                                 even though exposed at low tide)
			45  - water column
This dataset also includes lidar intensity values, number of returns, return number, time, and scan angle. The 100 meter buffered project area covers approximately 4,215 acres along the south central Pacific Coast of California near the town of Los Osos. LAS files were compiled in 500 m x 500 m tiles and clipped to the project boundary. The final classified lidar data were used to create topobathymetric bare earth DEMs in GeoTIFF format with 1m pixel resolution. This delivery of the Morro Bay 2022 dataset represents an area covering 97 - 500 m x 500 m LAS tiles clipped to the project boundary. This Project was completed in partnership between NOAA OCM and the NEP.

In addition to these lidar point data, the bare earth Digital Elevation Models (DEM) created from the lidar point data are also available. These data are available for custom download at the link provided in the URL section of this metadata record.

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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            <gco:CharacterString>This Project was completed in partnership between NOAA OCM and the Morro Bay National Estuary Program (NEP) to collect topobathymetric Lidar for the Morro Bay, California project area.
Data was collected to aid NOAA in assessing the channel morphology and topobathymetric surface of the study area to support and inform coastal resource and watershed managers on decisions relating to theBuilding Climate Resilience and Improving Water Quality through Eelgrass Restoration in Morro Bay project. This project monitors eelgrass, which declined between 2007 and 2011. The decline of eelgrass led to increased sediment erosion and, therefore, an effort to replant more eelgrass. Many organisms such as otters are reliant on the eelgrass for either food or shelter. Otters play a key role in restoration efforts by removing grazers. The lidar data will assist in quantifying change in eel grass distribution over time as well as sediment transport and sea level rise.</gco:CharacterString>
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            <gco:CharacterString>We request that you credit the National Oceanic and Atmospheric Administration (NOAA) when you use these data in a report, publication, or presentation. Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Office for Coastal Management (OCM)
			The custom download may be cited as National Oceanic and Atmospheric Administration (NOAA) Digital Coast Data Access Viewer.
         Charleston, SC: NOAA Office for Coastal Management.
         
         Accessed 2026-06-22 at https://coast.noaa.gov/dataviewer.
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                  <gco:CharacterString>Absolute accuracy was assessed using both Non-Vegetated Vertical Accuracy (NVA) survey methods. Survey checkpoints were evenly distributed as feasible throughout the project area. NVA compares known ground check point data that were withheld from the calibration and post-processing of the lidar point cloud to the triangulated surface generated from the ground classified lidar points. NVA is a measure of the accuracy of Lidar point data in open areas with level slope (less than 20 degrees) where the Lidar system has a high probability of measuring the ground surface and is evaluated at the 95% confidence interval (1.96*RMSE).
In the Morro Bay 2022 project area, 21 survey checkpoints were used to assess the non-vegetated vertical accuracy. Project specifications require NVA meet 0.196 m accuracy at the 95% confidence interval. Submerged topography points were tested separately. The Morro Bay 2022 area dataset Non-Vegetated Vertical Accuracy tested 0.049 m vertical accuracy at 95% confidence level against the the triangulated surface generated from the ground classified lidar points using 21 ground check points based on RMSEz (0.025 m) x 1.9600. 
In the Morro Bay 2022 project area, 72 survey checkpoints were used to assess the submerged topography accuracy against the triangulated surface generated from the bathymetric bottom classified lidar points. Project specifications require submerged topography shall meet a vertical RMSE of QL2b specified in the Draft National Coastal Mapping strategy 1.0 which is equivalent to 0.30 m RMSE at a depth of 1 m. The Morro Bay 2022 area dataset submerged topography accuracy tested 0.114 m vertical accuracy at the 95% confidence level against the triangulated surface generated from the bathymetric bottom classified points cloud using 72 submerged check points, based on RMSEz (0.058 m) x 1.9600. Submerged topography checkpoints usually occur in depths up to 1m.</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>Data covers the 97 tiles (500m x 500m tiles).</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>Not applicable</gco:CharacterString>
               </gmd:evaluationMethodDescription>
               <gmd:result gco:nilReason="missing"/>
            </gmd:DQ_ConceptualConsistency>
         </gmd:report>
         <gmd:lineage>
            <gmd:LI_Lineage>
               <gmd:statement>
                  <gco:CharacterString>NV5 Geospatial collected topobathy elevation data for the NOAA Office for Coastal Management (OCM) and the Morro Bay NEP (National Estuary Program). The data were processed to be available for custom download from the NOAA Digital Coast Data Access Viewer (DAV) and for bulk download from AWS S3.</gco:CharacterString>
               </gmd:statement>
               <gmd:processStep>
                  <gmd:LI_ProcessStep>
                     <gmd:description>
                        <gco:CharacterString>Data for the Morro Bay 2022 project area were acquired by Quantum Spatial (NV5) using Riegl VQ-880-GII Topobathy Lidar systems. All derived LAS data is referenced to: 
				Horizontal Datum-NAD83(2011) epoch: 2010.00
				Projection-UTM Zone 10N
				Horizontal Units-meters
				Vertical Datum-NAVD88 (Geoid12b)
				Vertical Units-meters   

				This Morro Bay 2022 redelivery dataset encompasses 97 - 500m x 500m tiles in southern California.

				Collected Lidar data were immediately processed by NV5 to a level that allowed QA/QC measures to determine if the sensor functioned properly and to assess the coverage of submerged topography. The initial files were inspected for sensor malfunctions and then passed through automated raster generation to develop an initial assessment of bathymetric coverage. NV5 reviewed all acquired flight lines to ensure complete coverage and positional accuracy of the laser points.

				NV5 resolved kinematic corrections for aircraft position data in PosPac MMS 8.5 using aircraft GNSS and Applanix's proprietary PP-RTX solution. This was used to correct continuous onboard measurements of aircraft position recorded throughout the flight. A final smoothed best estimate trajectory (SBET) was developed, blending post-processed aircraft position with attitude data. Using the SBETs, sensor head position and attitude were calculated throughout the survey.

				Following final SBET creation, NV5 used RiUnite 1.0.1 to calculate laser point positioning by associating SBET positions to each laser point return time. The speed of light and its direction of travel is changed or refracted when entering the water column from air. A refraction correction was applied to account for this difference by adjusting depth (distance traveled) and horizontal positioning (change of angle/direction) of all submerged points in the Lidar data. TerraSolid v19 and NV5's proprietary software LasMonkey were used to classify water surface points and derive water surface models. Separate models were created for each scanner of each collected swath to ensure temporal differences and wave or water surface height variations between flight lines were accurately accounted for when applying refraction correction to submerged data. These models, along with the Lidar points and the SBETs, were processed in LasMonkey's refraction tool to accurately adjust the positioning of bathymetric points. Using raster-based QC methods, output data were verified to ensure the refraction tool functioned properly. 

				Once all submerged points were refracted by flight line, data were exported to LAS 1.4 format and combined into 500 m x 500 m tiles. NV5 used custom algorithms in Terrascan v19 to classify the initial ground/submerged topography surface points. Data were further calibrated using StripAlign 2.1 based on classified hard surface areas of swath overlap. Relative accuracy was compared and verified through the use Delta-Z (DZ) orthos created using NV5's Las Product Creator. Absolute vertical accuracy of calibrated data were assessed using ground survey data and complete coverage was again verified. 

				After a final automated classification, NV5 performed manual editing to review all classification and improve the final Topobathymetric surface. NV5's LasMonkey software was used to update LAS header information, including all projection and coordinate reference system information. The final Lidar data are in LAS format 1.4 and point data record format 6.

				The final classification scheme is:
				1   - unclassified
				1O  - edge clip
				2   - ground
				7W  - low noise
				9   - NIR water surface
				18W - high noise
				40  - bathymetric bottom or submerged topography
				41  - Green water surface
                                43  - Submerged object, not otherwise specified (For Morro Bay, oyster reefs have this classification, even though exposed at low tide)
				45  - water column</gco:CharacterString>
                     </gmd:description>
                     <gmd:dateTime>
                        <gco:DateTime>2022-08-30T00:00:00</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 97 LAS files from NV5 Geospatial. The files contained lidar elevation and intensity measurements. The data were in UTM Zone 10N NAD83(2011), meters coordinates and NAVD88 (Geoid12B) elevations in meters. The point classifications were: 1 - Unclassified, 2 - Ground, 7 - Low Noise, 9 - Water, 18 - High Noise, 40 - Bathymetric Point, 41 - Water Surface, 45 - Water Column. OCM processed all point classes to the Digital Coast Data Access Viewer (DAV).

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

1. Internal OCM scripts were run to check the number of points by classification and by flight ID and the gps, elevation, and intensity ranges.

2. Internal OCM scripts were run on the las files to:

a. Convert from NAVD88 (Geoid12B) elevations to ellipsoid elevations

b. Convert from UTM Zone 10N NAD83 (2011), meters coordinates to geographic coordinates 

c. Assign the geokeys, to sort the data by gps time and zip the data to database and to the S3 Amazon bucket.</gco:CharacterString>
                     </gmd:description>
                     <gmd:dateTime>
                        <gco:DateTime>2022-10-05T00:00:00</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:processStep>
                  <gmd:LI_ProcessStep>
                     <gmd:description>
                        <gco:CharacterString>In February 2023, the NOAA Office for Coastal Management (OCM) received 3 LAS files from NV5 Geospatial. The files contained lidar elevation and intensity measurements and replace 3 existing files. The files are: MRR22_038, MRR22_046, and MRR22_055. These 3 files include class 43 points that are classified as "Submerged object, not otherwise specified (For Morro Bay, oyster reefs have this classification, even though exposed at low tide)." The data were in UTM Zone 10N NAD83(2011), meters coordinates and NAVD88 (Geoid12B) elevations in meters. The point classifications were: 1 - Unclassified, 2 - Ground, 7 - Low Noise, 9 - Water, 18 - High Noise, 40 - Bathymetric Point, 41 - Water Surface, 43 - Submerged Object, 45 - Water Column. OCM processed all point classes to the Digital Coast Data Access Viewer (DAV).

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

1. Internal OCM scripts were run to check the number of points by classification and by flight ID and the gps, elevation, and intensity ranges.

2. Internal OCM scripts were run on the las files to:

a. Convert from NAVD88 (Geoid12B) elevations to ellipsoid elevations

b. Convert from UTM Zone 10N NAD83 (2011), meters coordinates to geographic coordinates

c. Assign the geokeys, to sort the data by gps time and zip the data to database and to the S3 Amazon bucket.</gco:CharacterString>
                     </gmd:description>
                     <gmd:dateTime>
                        <gco:DateTime>2023-02-10T00:00:00</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>NV5 Geospatial</gco:CharacterString>
                           </gmd:title>
                           <gmd:date gco:nilReason="missing"/>
                           <gmd:citedResponsibleParty>
                              <gmd:CI_ResponsibleParty>
                                 <gmd:organisationName>
                                    <gco:CharacterString>NV5 Geospatial </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>2026-06-22</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>