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                <gco:CharacterString>Data for the Chesapeake Bay project was acquired by NOAA using a Riegl VQ-880-G sensor.  All delivered lidar data is referenced to:
Horizontal Datum-NAD83 (2011) epoch: 2010
Projection-UTM Zone 18 North
Horizontal Units-meters
Vertical Datum- NAD83 (2011) epoch: 2010
Vertical Units-meters

This dataset encompasses 1,527 1000m x 1000m tiles.  Both green lidar data and NIR lidar data were acquired.

NOAA acquired, calibrated, and performed the refraction correction of the lidar data.</gco:CharacterString>
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                <gco:CharacterString>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 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 algorithms in TerraScan to create the initial ground/submerged topography surface.

Dewberry used rasterized aggregate extents of refracted points to create automated 2-D breaklines with LAStools and ArcGIS. Light travels at different speeds in air versus water and its speed and direction of travel change when it enters the water column.  The refraction correction process accounts for this difference by adjusting the depth (distance traveled) and horizontal position (change of angle/direction) of the lidar points acquired within water. These breaklines delineate areas where the refraction correction was applied to the lidar data by Riegl's automated refraction correction software based on the software's detection of water. Where the automated process missed discrete water bodies that did not contain valid bathymetry (submerged topography) data, breaklines were manually drawn and added to a separate feature class to ensure the correct classification of the point cloud.

Dewberry used the 2-D refraction extents and additional bathy features 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 1.4 and point data record format 6.

The final classificaton scheme is as follows:
1-Unclassified
2-Ground
7- Noise
40- Bathymetric point
41- Water surface
43- Submerged object, not otherwise specified
45- Water column

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>
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