2012-2013 Post-Hurricane Sandy EAARL-B Submerged Topography - Barnegat Bay, New Jersey

Binary point-cloud data for part of Barnegat Bay, New Jersey, post-Hurricane Sandy (October 2012 hurricane), were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar, 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 55 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 0.5-1.6 meters. The nominal vertical elevation accuracy expressed as the root mean square error (RMSE) is 25 centimeters. A peak sampling rate of 15-30 kilohertz results in an extremely dense spatial elevation dataset. More than 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development.

The purpose of this project was to produce highly detailed and accurate digital elevation maps for part of Barnegat Bay, New Jersey, 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.

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Raw lidar data are not in a format that is generally usable by natural-resource managers and research 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 multitiered processing system developed originally by a USGS-NASA collaborative project. Specialized processing algorithms are used to convert raw waveform lidar data acquired by the EAARL-B 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 although first-surface data include vegetation, buildings, and other manmade structures, bare-earth data do not. The zero crossing of the second derivative (that is, detection of stationary points) is used to detect the first return, resulting in "first surface" topography, whereas the trailing edge algorithm (that is, the algorithm searches for the location before 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 part 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-B 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 GEOID12A model). Each file contains data located in a 2-kilometer by 2-kilometer tile, where the upper-left bound can be ascertained quickly through the filename. The first 3 numbers in the filename represent the left-most UTM east bounding coordinate (e###000) in meters, the next 4 numbers represent the top-most UTM north bounding coordinate (n####000) in meters, and the last 2 numbers (##)

represent the UTM zone in which the tile is located (for example, post_e123_n4567_18). The development of custom software for creating these data products has been supported by the U.S. Geological Survey CMGP's Lidar for Science and Resource Management project. Processed data products are used by the U.S. Geological Survey 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.

Lidar points in LAZ format (Class 11)

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

This data can be obtained on-line at the following URL:

https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=4730;

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The U.S. Geological Survey requests to be acknowledged as originators of these data in future products or derivative research.

The expected accuracy of the measured variables is as follows: attitude within 0.05 degree, 3 centimeters nominal ranging accuracy, and vertical elevation accuracy of 25 centimeters RMSE for the topographic surface. Quality checks are built into the data-processing software.

Expected horizontal accuracy for the Leica ALS70-cm sensor, as determined from system studies and other methods, is 1/5500th of the flight height, which, in the instance of this particular project was 3,800-feet AGL (1250m), giving a horizontal tolerance of less than 0.691 US survey feet (0.211 m).; Quantitative Value: 100 meters, Test that produced the value: 1.0 m

The nominal vertical elevation accuracy expressed as the root mean square error (RMSE) is 25 centimeters.; Quantitative Value: 0.25 meters, Test that produced the value: 25 cm RMSEz

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

Each file contains data located in a 2-kilometer by 2-kilometer tile where the upper-left bound can be ascertained quickly through the filename. The first 3 numbers in

the filename represent the left-most UTM east bounding coordinate (e###000) in meters,

the next 4 numbers represent the top-most UTM north bounding coordinate (n####000) in

meters, and the last 2 numbers (##) represent the UTM zone in which the tile is located

(for example, post_e123_n4567_18).