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            <gco:CharacterString>Between January and March 2010, lidar data was collected in southeast/coastal Georgia under a multi-agency partnership between the Coastal Georgia
Regional Development Center, USGS, FEMA, NOAA and local county governments. Data acquisition is for the full extent of coastal Georgia,
approximately 50 miles inland, excluding counties with existing high-resolution lidar derived elevation data. The data capture area consists
of an area of approximately 5703 square miles. This project is within the Atlantic Coastal Priority Area as defined by the National Geospatial
Program (NGP) and supports homeland security requirements of the National Geospatial-Intelligence Agency (NGA). This project also supports
the National Spatial Data Infrastructure (NSDI) and will advance USGS efforts related to The National Map and the National Elevation Dataset.

The data were delivered in LAS format version 1.2 in 5000 x 5000 foot tiles. The data are classified according to ASPRS LAS 1.2 classification
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Class  2 - Bare Earth
Class  7 - Low Point (Noise)
Class  9 - Water
Class 10 - Land below sea level
Class 12 - Overlap</gco:CharacterString>
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in coastal management decision making, including applications such as sea level rise and coastal flood mapping.

Lifts were planned to meet project specifications and were flown under cloud-free conditions in order to collect LiDAR points at an average
of 1.0 meter point spacing.  This allows the user to create Intensity Images, Break Lines, and fully Classified LiDAR LAS files.</gco:CharacterString>
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            <gco:CharacterString>Photo Science, Inc. acquired Brantley, Camden, Charlton, and Wayne Counties.  Fugro EarthData, Inc. acquired Bryan, Bulloch, Effingham, Long, McIntosh,
and Screven Counties.</gco:CharacterString>
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or exceed the project specifications which included:

1. Multiple Discrete Return, capable of at least 3 returns per pulse with Intensity values for each return.
2. Nominal Pulse Spacing (NPS) no greater than 1 meter with distribution of geometrically usable points expected to be uniform and free from
clustering.
3. Scan Angle (total Field-of-View (FOV)) should not exceed 40 degrees. Quality assurance on collections performed using scan angles wider than 34 degrees
will be particularly rigorous in the edge-of-swath areas.
4. Accuracy, The National Standard for Spatial Data Accuracy (NSSDA) of 95% confidence level, equal to (RMSEZ * 1.96) in a set of errors assumed
to be normally distributed. Fundamental Vertical Accuracy (FVA) of NSSDA RMSEZ = 18cm (NSSDA AccuracyZ 95% = 36 cm) or better; assessment
procedures to comply with FEMA guidelines.
5. Horizontal accuracy of 4 feet RMSE or better. Additionally, the Consolidated Vertical Accuracy (computed using NDEP and ASPRS methodology
in five (5) separate land cover classes (TBD)) shall meet ASPRS Class 1 (or National Map Accuracy Standard) guidelines for the generation
of 2 foot contours (Accuracyz = 36 cm). LiDAR data from different flight lines shall be consistent across flight lines, i.e., there is minimal
vertical offset within the noise level of the LiDAR system between adjacent flightlines. Maximum vertical offset between flightlines should be
no more than 6 cm.
6. Flightline overlap 20% or greater, as required to ensure there are no data gaps between the usable portions of the swaths.
7. Base stations for GPS surveys shall be based on first or second order survey control stations that are part of the National Geodetic Survey's
Spatial Reference System.
8. Collection Area: Defined Project Area, buffered by a minimum of 200*NPS.
9. Tide: +/- 2 hours of low tide.

Brantley and Wayne Counties were flown using an Optech Sensor.  Bryan, Bulloch, Charlton, Effingham, Long, McIntosh, and Screven Counties were flown
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; Quantitative Value: 0.196 meters, Test that produced the value: 
The vertical accuracy assessment compares the measured survey checkpoint elevations with those of the TIN as generated from the bare-earth LiDAR.
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coordinate values from the survey checkpoints.

Based on the vertical accuracy testing conducted by Dewberry using NSSDA and FEMA methodology, fundamental vertical accuracy (FVA) at the 95%
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                        <gco:CharacterString>Applanix software was used in the post processing of the airborne GPS and inertial data that is critical to the positioning and orientation
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processor to develop the point cloud from the LiDAR missions.  The point cloud is the mathematical three dimensional collection of all returns
from all laser pulses as determined from the aerial mission.  At this point this data is ready for analysis, classification, and filtering to
generate a bare earth surface model in which the above ground features are removed from the data set. The point cloud was manipulated within
the Optech or Leica software; GeoCue, TerraScan, and TerraModeler software was used for the automated data classification, manual cleanup,
and bare earth generation from this data.  Project specific macros were used to classify the ground and to remove the side overlap between
parallel flight lines.

All data was manually reviewed and any remaining artifacts removed using functionality provided by TerraScan and TerraModeler.

Class 2 LIDAR was used to create a bare earth surface model.  The surface model was then used to heads-up digitize 2D breaklines of inland
streams and rivers.  The National Elevation Dataset (1/3 arc-second) was used as a supplement to calculate streams with a contributing
drainage area of greater than 1 square mile.

Inland Ponds, Lakes, and Mudflats of 0.5 acres or greater were also collected along with the Coastal Shoreline.

Elevation values were assigned to all Inland Ponds, Lakes, and Shorelines using TerraModeler functionality.

Elevation values were assigned to all Inland streams, rivers, and mudflats using Photo Science proprietary software.

All Class 2 LIDAR data inside of the collected breaklines were then classified to Class 9 using TerraScan macro functionality.

The breakline files were then translated to ESRI Shapefile format using ESRI conversion tools.

Data was then run through additional macros to ensure deliverable classification levels matching LAS ASPRS Classification structure.
GeoCue functionality was then used to ensure correct LAS Version.  In house software was used as a final QA/QC check to provide LAS Analysis
of the delivered tiles.

Buffered LAS files were created in GeoCue to provide overedge to the DEM creation.  These tiles were then run through automated scripting
within ArcMap and were combined with the Hydro Flattened Breaklines to create the 4' DEM.  Final DEM tiles were clipped to the tile boundary
in order to provide a seamless dataset.

A manual QA review of the tiles was completed in ArcMap to ensure full coverage with no gaps or slivers within the project area.</gco:CharacterString>
                     </gmd:description>
                     <gmd:dateTime>
                        <gco:DateTime>2010-01-01T00:00:00</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 the files in las format. The files contained lidar elevation and intensity measurements.
The data were in State Plane projection (NAD83, Georgia East), and vertically referenced to NAVD88 using the Geoid 09 model.  Both horizontal
and vertical units were in feet.  OCM performed the following processing to the data to make it available within the Digital Coast:

1. The data were converted from Georgia State Plane coordinates to geographic (NAD83) coordinates.
2. The data were converted from orthometric (NAVD88) heights to ellipsoidal heights (GRS80) using Geoid 09.
3. The LAS data were sorted by latitude and the headers were updated.</gco:CharacterString>
                     </gmd:description>
                     <gmd:dateTime>
                        <gco:DateTime>2011-04-20T00:00:00</gco:DateTime>
                     </gmd:dateTime>
                  </gmd:LI_ProcessStep>
               </gmd:processStep>
               <gmd:source>
                  <gmd:LI_Source>
                     <gmd:description>
                        <gco:CharacterString>Source Contribution: LiDAR points were used to produce the deliverables. | Source Geospatial Form: digital data | Type of Source Media: Hard Drive</gco:CharacterString>
                     </gmd:description>
                     <gmd:sourceCitation>
                        <gmd:CI_Citation>
                           <gmd:title>
                              <gco:CharacterString>LiDAR</gco:CharacterString>
                           </gmd:title>
                           <gmd:date>
                              <gmd:CI_Date>
                                 <gmd:date>
                                    <gco:Date>2010-01-01</gco:Date>
                                 </gmd:date>
                                 <gmd:dateType>
                                    <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode"
                                                         codeListValue="publication">publication</gmd:CI_DateTypeCode>
                                 </gmd:dateType>
                              </gmd:CI_Date>
                           </gmd:date>
                        </gmd:CI_Citation>
                     </gmd:sourceCitation>
                     <gmd:sourceExtent>
                        <gmd:EX_Extent>
                           <gmd:temporalElement>
                              <gmd:EX_TemporalExtent>
                                 <gmd:extent>
                                    <gml:TimePeriod gml:id="sourceExtent-1139287">
                                       <gml:beginPosition>2010-01-28</gml:beginPosition>
                                       <gml:endPosition>2010-03-19</gml:endPosition>
                                    </gml:TimePeriod>
                                 </gmd:extent>
                              </gmd:EX_TemporalExtent>
                           </gmd:temporalElement>
                        </gmd:EX_Extent>
                     </gmd:sourceExtent>
                  </gmd:LI_Source>
               </gmd:source>
            </gmd:LI_Lineage>
         </gmd:lineage>
      </gmd:DQ_DataQuality>
   </gmd:dataQualityInfo>
</gmi:MI_Metadata>
