2009 USGS/NPS Experimental Advanced Airborne Research Lidar (EAARL): Cape Hatteras National Seashore - Post-Nor'easter Ida
This kmz file shows the extent of coverage for the 2009 USGS/NPS Cape Hatteras National Seashore Post-Nor'Easter Ida lidar data set.
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.
|Other Access||Online access information not available.|
|Distributor||DOC/NOAA/NOS/OCM > Office for Coastal Management, National Ocean Service, National
Oceanic and Atmospheric Administration, U.S. Department of Commerce
|Dataset Point of Contact||Amar Nayegandhi
Remote Sensing Specialist/Project Manager
Jacobs Technology, U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL
727 803-8747 (x3026)
Documentation links not available.
|Data Presentation Form:|| Digital image
|Dataset Progress Status||Complete|
|Data Update Frequency:||Not planned|
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). The input parameters for the random consensus filter (RCF) for these data were: grid cell size (buffer) = 6 meters x 6 meters; vertical tolerance (vertical width) = 500 centimeters. 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.
|Purpose:||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.|
|Time Period:||Unknown to Unknown|
|Spatial Reference System:||urn:ogc:def:crs:EPSG::4269|
|Spatial Bounding Box Coordinates:||
|Spatial Coverage Map:|
|Use Constraints||No constraint information available|
|Fees||Fee information not available.|
Last Modified: 2013-06-04
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