2009 USGS/NPS Experimental Advanced Airborne Research Lidar (EAARL): Cape Hatteras National Seashore - Post-Nor'easter Ida

This is a bare-earth data lidar data set that was collected on November 27, 29 and December 1, 2009 along the shoreline of the Cape

Hatteras National Seashore in Dare and Hyde Counties in North Carolina, after Nor'easter Ida.

Binary point-cloud data were produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological

Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over the area using the Experimental Advanced Airborne

Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal

topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage.

The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The

plane travels over the target area at approximately 50 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of

approximately 240 meters with an average point spacing of 2-3 meters. The EAARL, developed originally by NASA at Wallops Flight Facility in Virginia,

measures ground elevation with a vertical resolution of 15 centimeters. A sampling rate of 3 kilohertz or higher, results in an extremely dense spatial

elevation dataset. Over 100 kilometers of coastline can be easily surveyed within a 3- to 4-hour mission. When subsequent elevation maps for an area

are analyzed, they provide a useful tool to make management decisions regarding land development.

Original contact information:

Contact Name: Amar Nayegandhi

Contact Org: Jacobs Technology, U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL

Title: Remote Sensing Specialist/Project Manager

Phone: 727 803-8747 (x3026)

Email: anayegandhi@usgs.gov

The purpose of this project was to produce highly detailed and accurate digital elevation maps of a portion of the Cape Hatteras National Seashore

in Dare and Hyde Counties in North Carolina, post-Nor'Ida (November 2009 nor'easter), for use as a management tool and to make these data available

to natural-resource managers and research scientists.

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Raw lidar data are not in a format that is generally usable by resource managers and scientists for scientific analysis. Converting dense lidar

elevation data into a readily usable format without loss of essential information requires specialized processing. The U.S. Geological Survey's

Coastal and Marine Geology Program (CMGP) has developed custom software to convert raw lidar data into a GIS-compatible map product to be provided

to GIS specialists, managers, and scientists. The primary tool used in the conversion process is Airborne Lidar Processing System (ALPS), a

multi-tiered processing system developed by a USGS-NASA collaborative project. Specialized processing algorithms are used to convert raw waveform

lidar data acquired by the EAARL to georeferenced spot (x,y,z) returns for "first surface" and "bare earth" topography. The terms first surface and

bare earth refer to the digital elevation data of the terrain, but while first-surface data includes vegetation, buildings, and other man-made

structures, bare-earth data does not. The zero crossing of the second derivative (that is, detection of local maxima) is used to detect the first

return, resulting in "first surface" topography, while the trailing edge algorithm (that is, the algorithm searches for the location prior to the

last return where direction changes along the trailing edge) is used to detect the range to the last return or "bare earth" (the first and last

returns being the first and last significant measurable portion of the return pulse). Statistical filtering, known as the Random Consensus

Filter (RCF), is used to remove false bottom returns and other outliers from the EAARL topography data. The filter uses a grid of non-overlapping

square cells (buffer) of user-defined size overlaid onto the original point cloud. The user also defines the vertical tolerance (vertical width)

based on the topographic complexity and point sampling density of the data. The maximum allowable elevation range within a cell is established by

this vertical tolerance. An iterative process searches for the maximum concentration of points within the vertical tolerance, and removes those

points outside of the tolerance (Nayegandhi and others, 2009). These data are then converted to the North American Datum of 1983 and the North

American Vertical Datum of 1988 (using the GEOID09 model).

The development of custom software for creating these data products has been supported by the U.S. Geological Survey CMG Program's Decision Support

for Coastal Science and Management project. Processed data products are used by the U.S. Geological Survey CMG Program'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.

A footprint of this data set may be viewed in Google Earth at:

https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/1071/supplemental/2009_USGS_NPS_Cape_Hatteras_National_Seashore_Lidar.kmz

The input parameters for the random consensus filter (RCF) were: grid cell size (buffer) = 6 meters x 6 meters; vertical tolerance

(vertical width) = 500 centimeters.

http://pubs.usgs.gov/of/2009/1078/

Although these data have been processed successfully on a computer system at the U.S. Geological Survey, 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 U.S. Geological Survey shall not be held liable for improper or incorrect use of the data described and/or contained herein.

Neither the U.S. Government, the Department of the Interior, nor the USGS, nor any of their employees, contractors, or subcontractors, make any warranty,

expressed or implied, nor assume any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus,

product, or process disclosed, nor represent that its use would not infringe on privately owned rights.

Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office for Coastal Management or its partners.

Unclassified

None

This data can be obtained on-line at the following URL: https://coast.noaa.gov/dataviewer;

None

Users should be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no

longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its

limitations.

Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 2; ESRI ArcCatalog 9.2.2.1350

The expected accuracy of the measured variables is as follows: attitude within 0.07 degree, 3 centimeters nominal ranging accuracy, and vertical

elevation accuracy of +/-15 centimeters for the topographic surface. Quality checks are built into the data-processing software.

Raw elevation measurements have been determined to be within 1 meter in horizontal accuracy.

Typical vertical elevation accuracies for these data are consistent with the point elevation data, +/-15 centimeters. However, a ground-control

survey is not conducted simultaneously with every lidar survey. Vertical accuracies may vary based on the type of terrain and the accuracy of the

GPS and aircraft-attitude measurements.

These point-cloud data may appear sparse or nonexistent, which is a result of removal from manual editing or lack of survey coverage.

The original files as received by NOAA OCM, contained data located in a 10-kilometer by 10-kilometer tile where the upper-left bound can be

assessed quickly through the filename. The first 3 numbers in the filename represent the left-most UTM easting coordinate (e###000) in meters,

the next 4 numbers represent the top-most UTM northing coordinate (n####000) in meters, and the last 2 numbers (##) represent the UTM zone in

which the tile is located (for example, fs_e123_n4567_18).