U.S. Geological Survey 2013 first remote-sensing image U.S. Geological Survey Data Series 765 St. Petersburg, FL U.S. Geological Survey http://pubs.usgs.gov/ds/765/ Dune features (dune crest and toe elevations) and mean-high-water shoreline data for a portion of the New York, Delaware, Maryland, Virginia, and North Carolina coastlines, post-Hurricane Sandy (Sandy was an October 2012 hurricane that made landfall as an extratropical cyclone on the 29th), were produced by the U.S. Geological Survey (USGS) from remotely sensed, geographically referenced elevation measurements collected by Photo Science and Woolpert using using airborne lidar sensors. Binary point-cloud data, as well as digital elevation models (DEM), were also produced by Photo Science and Woolpert and are included in this Data Series. The purpose of this project was to derive shoreline, dune crest (Dhigh), and dune toe (Dlow) of a portion of the New York, Delaware, Maryland, Virginia, and North Carolina coastlines, post-Hurricane Sandy (October 2012 hurricane), for use as a management tool and to make these data available to natural-resource managers and research scientists. Processed data products are used by the USGS CMGP's National Assessments of Coastal Change Hazards project to quantify the vulnerability of shorelines to coastal change hazards such as severe storms, sea-level rise, and shoreline erosion and retreat. 20121105 20121108 20121109 20121110 20121111 20121112 20121116 20121126 20121128 20121129 ground condition Complete None planned -78.8255 -72.6947 40.8128 34.5574 ISO 19115 Topic Category elevation USGS Metadata Identifier USGS:f692f2b9-1e99-4556-8a88-0bb8cd8d1547 General Cessna 206 Cessna 310 Dhigh Dlow Digital Elevation Model DEM dune crest dune toe extratropical cyclone laser altimetry lidar remote sensing shoreline topography Global Change Master Science Directory LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION OCEAN > COASTAL PROCESSES > BARRIER ISLANDS OCEAN > COASTAL PROCESSES > BEACHES OCEAN > COASTAL PROCESSES > SHORELINE DISPLACEMENT DOI/USGS/CMG > COASTAL AND MARINE GEOLOGY, U.S. GEOLOGICAL SURVEY, U.S. DEPARTMENT OF INTERIOR GCMD Instrument LIDAR > LIGHT DETECTION AND RANGING Data Categories for Marine Planning distributions bathymetry and elevation Marine Realms Information Bank (MRIB) Keywords altimetry topographic mapping USGS Thesaurus LIDAR topography digital elevation models Geographic Names Information System Delaware Maryland Fire Island Long Island New York North Carolina Virginia DelMarVa Peninsula United States General Bare Earth General 2012 Post-Hurricane Sandy None The U.S. Geological Survey and National Park Service request to be acknowledged as originators of these data in future products or derivative research. Hilary Stockdon U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL Research Oceanographer mailing and physical address

600 4th Street South

St. Petersburg FL 33701 USA 727 803-8747 (x3074) 727 803-2031 hstockdon@usgs.gov Acknowledgment of the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, as a data source would be appreciated in products developed from these data, and such acknowledgment as is standard for citation and legal practices for data source would be appreciated. Sharing of new data layers developed directly from these data would also be appreciated by the U.S. Geological Survey staff. Users should be aware that comparisons with other datasets for the same area from other time periods may be inaccurate due to inconsistencies resulting from changes in photointerpretation, mapping conventions, and digital processes over time. These data are not legal documents and are not to be used as such. Unclassified Unclassified None Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 2; ESRI ArcCatalog 9.3.1.3000 The project area required lidar to be collected on 1 meter ground sample distance (GSD) or better and processed to meet a bare earth vertical accuracy of 12.5 centimeters RMSEz or better. This metadata file is generalized; each data file has a corresponding metadata file. These data span from Long Island, New York to Cape Hatteras, North Carolina. The state of New Jersey was collected using the EAARL-B sensor and that data will be published separately. Horizontal accuracy is +/- 0.194 meter at the 95% confidence level. LAS data were compared to survey control points to determine the FVA of the LAS Swath and of the DEM. LAS Swath Fundamental Vertical Accuracy (FVA) Tested 0.147m (14.7cm) fundamental vertical accuracy at a 95 percent confidence level in open terrain using 0.075m (7.5cm) (RMSEz x 1.96000). Tested against the TIN. Bare-Earth DEM Fundamental Vertical Accuracy (FVA) Tested 0.147m (14.7cm) fundamental vertical accuracy at a 95 percent confidence level, derived according to NSSDA, in open terrain using 0.075m (7.5cm) (RMSEz x 1.96000). Tested against the DEM. Using an Optech Gemini LiDAR Sensor, 11 flight lines of high density data, at a nominal pulse spacing (NPS) of 1 meter, were collected by Woolpert along the southern shore of Long Island, New York (approximately 15 square miles). Data Acquisition Height = 3,500 feet AGL - Aircraft Speed = 125 Knots. Multiple returns were recorded for each laser pulse along with an intensity value for each return. A total of on (1) mission was flown on November 05. Two airborne global positioning system (GPS) base stations were used in support of the lidar data acquisition. Eight ground control points were surveyed through static methods. The GEOID used to reduce satellite derived elevations to orthometric heights was GEOID96. Data for the task order is referenced to the UTM Zone 18N, North American Datum of 1983 (NAD83), and North American Vertical Datum of 1988 (NAVD88), in meters. Airborne GPS data were differentially processed and integrated with the post-processed IMU data to derive a smoothed best estimate of trajectory (SBET). The SBET was used to reduce the lidar slant range measurements to a raw reflective surface for each flight line. The coverage was classified to extract a bare earth digital elevation model (DEM) and separate last returns. In addition to the LAS deliverables, one layer of coverage was delivered in the Imagine (IMG) Format: bare-earth. 20121105 Woolpert, Inc. Geospatial Services mailing and physical address

4454 Idea Center Blvd.

Dayton OH 45430 USA 937 461-5660 937 461-0743 The lidar calibration and system performance is verified on a periodic basis using Woolpert's calibration range. The calibration range consists of a large building and runway. The edges of the building and control points along the runway have been located using conventional survey methods. Inertial measurement unit (IMU) misalignment angles and horizontal accuracy are calculated by comparing the position of the building edges between opposing flight lines. The scanner scale factor and vertical accuracy is calculated through comparison of lidar data against control points along the runway. Field calibration is performed on all flight lines to refine the IMU misalignment angles. IMU misalignment angles are calculated from the relative displacement of features within the overlap region of adjacent (and opposing) flight lines. The raw lidar data is reduced using the refined misalignment angles. 2012 Woolpert, Inc. Geospatial Services mailing and physical address

4454 Idea Center Blvd.

Dayton OH 45430 USA 937 461-5660 937 461-0743 Once the data acquisition and GPS processing phases are complete, the lidar data were processed immediately by Woolpert to verify the coverage had no voids. The GPS and IMU data was post processed using differential and Kalman filter algorithms to derive a best estimate of trajectory. The quality of the solution was verified to be consistent with the accuracy requirements of the project. 20121107 Woolpert, Inc. Geospatial Services mailing and physical address

4454 Idea Center Blvd.

Dayton OH 45430 USA 937 461-5660 937 461-0743 The individual flight lines were inspected by Woolpert to ensure the systematic and residual errors have been identified and removed. Then, the flight lines were compared to adjacent flight lines for any mismatches to obtain a homogenous coverage throughout the project area. The point cloud underwent a classification process to determine bare-earth points and non-ground points utilizing "first and only" as well as "last of many" lidar returns. This process determined Default (Class 1), Ground (Class 2), Noise (Class 7), Water (Class 9), Ignored Ground (Class 10), Overlap Default (Class 17), and Overlap Ground (class 18) classifications. The bare-earth (Class 2 - Ground) lidar points underwent a manual QA/QC step to verify that artifacts have been removed from the bare-earth surface. The surveyed ground control points are used to perform the accuracy checks and statistical analysis of the lidar dataset. 20121107 Woolpert, Inc. Geospatial Services mailing and physical address

4454 Idea Center Blvd.

Dayton OH 45430 USA 937 461-5660 937 461-0743 Photo Science, Inc. located a total of 29 calibration control points used in the post processing of the lidar data. The points were located on relatively flat terrain on surfaces that generally consisted of grass, gravel, or bare earth. Applanix software was used in the post processing of the airborne GPS and inertial data that is critical to the positioning and orientation of the sensor during all flights. POSPac MMS provides the smoothed best estimate of trajectory (SBET) that is necessary for Optech or Leica's post 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. The GEOID used to reduce satellite derived elevations to orthometric heights was GEOID96. Data for the task order are referenced to the UTM Zone 18N, NAD83, and NAVD88, in meters. At this point the data are ready for analysis, classification, and filtering to generate a bare-earth surface model in which the above ground features are removed from the dataset. The point cloud was manipulated within the Optech or Leica software; GeoCue, TerraScan, and TerraModeler software were used for the automated data classification, manual cleanup, and bare earth generation from the data. Project specific macros were used to classify the ground and to remove the side overlap between parallel flight lines. All data were manually reviewed and any remaining artifacts removed using functionality provided by TerraScan and TerraModeler. All ground (ASPRS Class 2) lidar data inside of the Lake Pond and Double Line Drain hydro flattening breaklines were then classified to water (ASPRS Class 9) using TerraScan macro functionality. All Lake Pond Island and Double Line Drain Island features were checked to ensure that the ground (ASPRS Class 2) were reclassified to the correct classification after the automated classification was completed. All overlap data were processed through automated functionality provided by TerraScan to classify the overlapping flight line data to approved classes by USGS. The overlap data were classified to Class 17 (USGS Overlap Default) and Class 18 (USGS Overlap Ground). These classes were created through automated processes only and were not verified for classification accuracy. Data were then run through additional macros to ensure deliverable classification levels matching the ASPRS LAS Version 1.2 Classification structure. GeoCue functionality was then used to ensure correct LAS Versioning. In-house software was used as a final QA/QC check to provide LAS Analysis of the delivered tiles. QA/QC checks were performed on a per tile level to verify final classification metrics and full LAS header information. 2012 Photo Science, Inc. Geospatial Services mailing and physical address

4454 Idea Center Blvd.

Lexington KY 40503 USA 859 277-8700 All Photo Science elevation points classified as ground (class 2), water (class 9), and unclassified (class 1) were extracted from the .las files and converted to ASCII xyz point files using LASTools las2las.exe. The ASCII point files were then written to netcdf format using MATLAB 8.0.0.783. 20130227 Kristin Sopkin Cherokee Nation Technology Solutions, U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL Data Modeler/Analyst mailing and physical address

600 4th Street South

St. Petersburg FL 33701 USA 727 803-8747 (x3141) ksopkin@usgs.gov All Woolpert .laz files were extracted to .las and converted to ASCII xyz point files using LASTools las2las.exe. The ASCII point files were then written to netcdf format using MATLAB 8.0.0.783. 20130227 Kristin Sopkin Cherokee Nation Technology Solutions, U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL Data Modeler/Analyst mailing and physical address

600 4th Street South

St. Petersburg FL 33701 USA 727 803-8747 (x3141) ksopkin@usgs.gov Elevation data from lidar surveys were interpolated in MATLAB 8.0.0.783 to a gridded domain that was rotated parallel to the shoreline and had a resolution of 10 meters in the longshore direction and 2.5 meters in the cross-shore direction. The interpolation method applies spatial filtering with a Hanning window that is twice as wide as the grid resolution. The shoreline position was determined as the intersection of the 20-year mean high water contour line with the cross-shore profiles of the gridded elevations at 10-meter intervals along the coast using MATLAB 8.0.0.783. Reference for 20-year mean high water line: Weber, K.M., List, J.H., and Morgan, K.L.M., 2005, An operational mean high water datum for determination of shoreline position from topographic lidar data: U.S. Geological Survey Open-File Report 2005-1027, available at http://pubs.usgs.gov/of/2005/1027/. 20130409 Kristin Sopkin Cherokee Nation Technology Solutions, U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL Data Modeler/Analyst mailing and physical address

600 4th Street South

St. Petersburg FL 33701 USA 727 803-8747 (x3141) ksopkin@usgs.gov Elevation data from lidar surveys were interpolated in MATLAB 8.0.0.783 to a gridded domain that was rotated parallel to the shoreline and had a resolution of 10 meters in the longshore direction and 2.5 meters in the cross-shore direction. The interpolation method applies spatial filtering with a Hanning window that is twice as wide as the grid resolution. The position and height of the crest of the primary dune were then extracted from cross-shore profiles of the gridded elevations at 10-meter intervals along the coast using an automated algorithm in MATLAB 8.0.0.783. Dune crest height was then interpolated to the 20-year mean high water line over 1-kilometer sections of coast and smoothed using a Hanning window with a width of 2 kilometers. Reference for automated algorithm: Stockdon, H.F., Doran, K.J., Thompson, D.M., Sopkin, K.L., Plant, N.G., and Sallenger, A.H., 2012, National assessment of hurricane-induced coastal erosion hazards: Gulf of Mexico: U.S. Geological Survey Open-File Report 2012-1084, 51 p. 20130409 Kristin Sopkin Cherokee Nation Technology Solutions, U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL Data Modeler/Analyst mailing and physical address

600 4th Street South

St. Petersburg FL 33701 USA 727 803-8747 (x3141) ksopkin@usgs.gov Elevation data from lidar surveys were interpolated in MATLAB 8.0.0.783 to a gridded domain that was rotated parallel to the shoreline and had a resolution of 10 meters in the longshore direction and 2.5 meters in the cross-shore direction. The interpolation method applies spatial filtering with a Hanning window that is twice as wide as the grid resolution. The position and height of the primary dune toe, defined as the location of maximum change in slope between the shoreline and the primary dune crest for each cross-shore profile, were then extracted from the gridded elevations at 10-meter intervals along the coast using an automated algorithm in MATLAB 8.0.0.783. Dune toe elevation was then interpolated to the 20-year mean high water line over 1-kilometer sections of coast and smoothed using a Hanning window with a width of 2 kilometers. Reference for automated algorithm: Stockdon, H.F., Doran, K.J., Thompson, D.M., Sopkin, K.L., Plant, N.G., and Sallenger, A.H., 2012, National assessment of hurricane-induced coastal erosion hazards: Gulf of Mexico: U.S. Geological Survey Open-File Report 2012-1084, 51 p. 20130409 Kristin Sopkin Cherokee Nation Technology Solutions, U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL Data Modeler/Analyst mailing and physical address

600 4th Street South

St. Petersburg FL 33701 USA 727 803-8747 (x3141) ksopkin@usgs.gov Dune crest and toe were interpolated in Matlab (version 2012a) and smoothed to a 1 km alongshore spacing using a hanning window filter. Sections with greater than 75 percent of data missing are flagged with the invalid number of 999. The 1 km smoothed dune crest, toe and rms errors for each were written to line shapefiles using Matlab's shapewrite.m script. Shoreline position was exported from Matlab into point shapefiles and converted to lines using XTools Pro for ArcGIS desktop (version 9.1). The resulting line connected points across inlets and channels, so these areas were hand-edited in ArcMap (version 10.1). 20130418 Kara Doran U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL Research Assistant mailing and physical address

600 4th Street South

St. Petersburg FL 33701 USA 727 803-8747 (x3117) kdoran@usgs.gov Metadata imported into ArcCatalog 9.3.1.3000 from XML file. 20130226 Xan Fredericks Cherokee Nation Technology Solutions, U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL Lidar Validation and Processing Analyst mailing and physical address

600 4th Street South

St. Petersburg FL 33701 USA 727 803-8747 (x3086) afredericks@usgs.gov Keywords section of metadata optimized for discovery in USGS Coastal and Marine Geology Data Catalog. 20170124 U.S. Geological Survey Alan O. Allwardt Contractor -- Information Specialist mailing and physical address

2885 Mission Street

Santa Cruz CA 95060 831-460-7551 831-427-4748 aallwardt@usgs.gov Added keywords section with USGS persistent identifier as theme keyword. 20201013 U.S. Geological Survey VeeAnn A. Cross Marine Geologist mailing and physical

384 Woods Hole Road

Woods Hole MA 02543-1598 508-548-8700 x2251 508-457-2310 vatnipp@usgs.gov Tiling Index Raster Pixel Universal Transverse Mercator 18 0.999600 -75.000000 0 500000.000000 0 row and column 1.00000 1.00000 meters North American Datum of 1983 Geodetic Reference System 80 6378137.000000 298.25722210100002 North American Vertical Datum of 1988 0.15 meters Explicit elevation coordinate included with horizontal coordinates The morphological features that define the beach system, the location and height of the crest and toe (base) of the seaward dune and the shoreline location, are extracted from the lidar elevations. These values are used to quantify coastal change, such as dune erosion due to storm impacts, when compared with dune morphology derived from lidar surveys conducted prior to storm arrival. Dune features are also coupled with storm hydrodynamics predictions to determine the vulnerability of sections of coastline to dune erosion, overwash and inundation. Stockdon, H.F., Doran, K.J., Thompson, D.M., Sopkin, K.L., Plant, N.G., and Sallenger, A.H., 2012, National assessment of hurricane-induced coastal erosion hazards: Gulf of Mexico: U.S. Geological Survey Open-File Report 2012-1084, 51 p. U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL Hilary Stockdon Research Oceanographer mailing and physical address

600 4th Street South

St. Petersburg FL 33701 USA 727 803-8747 (x3074) DS 765 Although these data have been processed successfully on a computer system at the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system, or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. The USGS shall not be held liable for improper or incorrect use of the data described and/or contained herein. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. IMG 1 IMG Vary 20230927 Xan Fredericks Cherokee Nation Technology Solutions, U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL Lidar Validation and Processing Analyst mailing and physical address

600 4th Street South

St. Petersburg FL 33701 USA 727 803-8747 (x3086) afredericks@usgs.gov FGDC Content Standards for Digital Geospatial Metadata FGDC-STD-001-1998 local time