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2012 USACE Post-Hurricane Sandy Topographic LiDAR: Coastal Connecticut

browse graphicThis kmz file shows the extent of coverage for the 2012 USACE Post-Hurricane Sandy Coastal Connecticut lidar data set.
These topographic elevation data have been acquired and developed by the U.S. Corps of Engineers St. Louis District for a 116 sq. mile project area encompassing the entire coastal region of the State of Connecticut. Using an ALS-60 MPiA sensor mounted on a Cessna 310 twin engine aircraft, Fugro EarthData, Inc. collected LiDAR point measurements over the project area with a 1.0 meter, nominal post spacing. The collection for the was accomplished between November 14, 2012 and November 16, 2012; 46 flight lines were acquired in 4 lifts. The lines were flown at an average of 1825 meters feet above mean terrain using a pulse rate of 123,700 pulses per second. Multiple returns of x,y,z and intensity were acquired. The processed LiDAR classified according to LAS version 1.2 format standard: 1 unclassified, 2 ground, 7 low points, 8 model keypoints, 9 water, and 10 ignored points.
Cite this dataset when used as a source.
Online Access
  • Online access is not available for this resource
Distribution Formats
  • LAZ
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 US Army Corps of Engineers St. Louis District
Documentation links not available.
  • publication: 2013-01-01
Data Presentation Form: Digital image
Dataset Progress Status Complete
Data Update Frequency: As needed
Purpose: To acquire, process and store multiple-return LiDAR calibrated and classified point cloud data using compliant LAS 1.2 format with the following collection conditions: Atmospheric: cloud and fog free between aircraft and ground; Ground Vegetation: leaf off preferred; Flight Height: as required to acquire point data sufficient to meet requirements. Additionally the LiDAR data must collected at or below MLW tidal elevation 0 whenever possible.
Use Limitations
  • These data depict the elevations at the time of the survey and are only accurate for that time. 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be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions.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. Any conclusions drawn from analysis of this information are not the responsibility of NOAA or any of its partners. These data are NOT to be used for navigational purposes.
  • DOC/NOAA/NOS/OCM > Office for Coastal Management, National Ocean Service, National Oceanic and Atmospheric Administration, U.S. Department of Commerce
  • US Army Corps of Engineers (USACE) St. Louis District
  • DOC/NOAA/NOS/OCM > Office for Coastal Management, National Ocean Service, National Oceanic and Atmospheric Administration, U.S. Department of Commerce
Time Period: 2012-11-14 to 2012-11-16
Spatial Reference System: urn:ogc:def:crs:EPSG::4269 Ellipsoid in Meters
Spatial Bounding Box Coordinates:
N: 41.396254
S: 40.951486
E: -71.847828
W: -73.661202
Spatial Coverage Map:
Theme keywords
  • Bathymetry/Topography
  • LiDAR
  • LAS
  • Elevation
Place keywords
  • US
  • Connecticut
  • Coast
Use Constraints No constraint information available
Fees Fee information not available.
Lineage information for: dataset
  • Fugro EarthData, Inc.
  • Fugro EarthData, Inc.
  • Fugro EarthData, Inc.
  • DOC/NOAA/NOS/OCM > Office for Coastal Management, National Ocean Service, National Oceanic and Atmospheric Administration, U.S. Department of Commerce
  • DOC/NOAA/NESDIS/NCEI > National Centers of Environmental Information, NESDIS, NOAA, U.S. Department of Commerce
Processing Steps
  • 2012-11-18T00:00:00 - All acquired LiDAR data went through a preliminary review to assure that complete coverage was obtained and that there were no gaps between flight lines before the flight crew left the project site. Once back in the office, the data is run through a complete iteration of processing to ensure that it is complete, uncorrupted, and that the entire project area has been covered without gaps between flight lines. There are essentially three steps to this processing: 1) GPS/IMU Processing - Airborne GPS and IMU data was immediately processed using the airport GPS base station data, which was available to the flight crew upon landing the plane. This ensured the integrity of all the mission data. These results were also used to perform the initial LiDAR system calibration test. 2) Raw LiDAR Data Processing - Technicians processed the raw data to LAS format flight lines with full resolution output before performing QC. A starting configuration file was used in this process, which contains the latest calibration parameters for the sensor. The technician also generated flight line trajectories for each of the flight lines during this process. 3) Verification of Coverage and Data Quality - Technicians checked flight line trajectory files to ensure completeness of acquisition for project flight lines, calibration lines, and cross flight lines. The intensity images were generated for the entire lift at the required post spacing for the project. The technician visually checked the intensity images against the project boundary to ensure full coverage. The intensity histogram was analyzed to ensure the quality of the intensity values. The technician also thoroughly reviewed the data for any gaps in project area. The technician generated a few sample TIN surfaces to ensure no anomalies were present in the data. Turbulence was inspected for and if it affected the quality of the data, the flight line was rejected and reflown. The technician also evaluated the achieved post spacing against project specified post spacing.
  • 2012-11-19T00:00:00 - The boresight for each lift was done individually as the solution may change slightly from lift to lift. The following steps describe the Raw Data Processing and Boresight process: 1) Technician processed the raw data to LAS format flight lines using the final GPS/IMU solution. This LAS data set was used as source data for boresight. 2) Technician first used commercial software to calculate initial boresight adjustment angles based on sample areas selected in the lift- mini project. These areas cover calibration flight lines collected in the lift, cross tie and production flight lines. These areas are well distributed in the lift coverage and cover multiple terrain types that are necessary for boresight angle calculation. The technician then analyzed the result and made any necessary additional adjustment until it is acceptable for the mini project. 3) Once the boresight angle calculation was done for the mini project, the adjusted settings were applied to all of the flight lines of the lift and checked for consistency. The technician utilized commercial and proprietary software packages to analyze the matching between flight line overlaps for the entire lift and adjusted as necessary until the results met the project specifications. 4) Once the boresight adjustment was completed for each lift individually, the technician ran a routine to check the vertical misalignment of all flight lines in the project and also compared data to ground truth. The entire dataset was then adjusted to ground control points. 5) The technician ran a final vertical accuracy check between the adjusted data and surveyed ground control points after the z correction. The result was analyzed against the project specified accuracy to make sure it meets the project requirements
  • 2012-11-27T00:00:00 - Once boresighting is complete for the project, the project was set up for classification. The LiDAR data was cut to production tiles. The flight line overlap points, Noise points and Ground points were classified automatically in this process. Fugro EarthData, Inc. has developed a unique method for processing LiDAR data to identify and re-classify elevation points falling on vegetation, building, and other above ground structures into separate data layers. The steps are as follows: 1) Fugro EarthData, Inc. utilized commercial software as well as proprietary software for automatic filtering. The parameters used in the process were customized for each terrain type to obtain optimum results. 2) The Automated Process typically re-classifies 90-98% of points falling on vegetation depending on terrain type. Once the automated filtering was completed, the files were run through a visual inspection to ensure that the filtering was not too aggressive or not aggressive enough. In cases where the filtering was too aggressive and important terrain features were filtered out, the data was either run through a different filter or was corrected during the manual filtering process. 3) Interactive editing was completed in 3D visualization software which also provides manual and automatic point classification tools. Fugro EarthData, Inc. used commercial and proprietary software for this process. Vegetation and artifacts remaining after automatic data post-processing were reclassified manually through interactive editing. The hard edges of ground features that were automatically filtered out during the automatic filtering process were brought back into ground class during manual editing. Auto-filtering routines were utilized as much as possible within fenced areas during interactive editing for efficiency. The technician reviewed the LiDAR points with color shaded TINs for anomalies in ground class during interactive filtering. 4) All LAS tiles went through peer review after the first round of interactive editing was finished. This helps to catch misclassification that may have been missed by the interactive editing. 5) Upon the completion of peer review and finalization of bare earth filtering, the classified LiDAR point cloud work tiles went through a water classification routine based on the collected water polygons. 6) The time stamps for all points were converted to Adjusted Standard GPS time using proprietary software developed by Fugro EarthData, Inc. The data collection date and the current GPS time stamp were used in calculating the Adjusted Standard GPS time. 7) The classified point cloud data were packaged into geographic Coordinates, NAD83(NA2011) in meters and the vertical datum is the North American Vertical Datum of 1988 (NAVD88) in meters using GEIOD09 for delivery. The data was also cut to the approved tile layout and clipped to the approved project boundary. The technician checked the output LAS files for coverage and format; d) the technician then QCd the dataset for quality assurance and enhanced the Bare Earth classification in the project area for consistent data quality; ie) these final LiDAR tiles were then used in the hydro flattening process. 8) classified LiDAR point cloud data are delivered in LAS 1.2 format: 1 unclassified, 2 ground, 7 low points, 8 model keypoints, 9 water, and 10 ignored points.
  • 2013-01-01T00:00:00 - The NOAA Coastal Services Center (CSC) received topographic files in LAS format. The files contained lidar elevation and intensity measurements. The data were received in Geographic (NAD83) coordinates and were vertically referenced to NAVD88 using the Geoid12a model. The vertical units of the data were meters. CSC performed the following processing for data storage and Digital Coast provisioning purposes: 1. The topographic las files were converted from orthometric (NAVD88) heights to ellipsoidal heights using Geoid12a. 2. The data were converted to LAZ format.
  • 2013-02-20T00:00:00 - The NOAA National Geophysical Data Center (NGDC) received lidar data files via ftp transfer from the NOAA Coastal Services Center. The data are currently being served via NOAA CSC Digital Coast at The data can be used to re-populate the system. The data are archived in LAS or LAZ format. The LAS format is an industry standard for LiDAR data developed by the American Society of Photogrammetry and Remote Sensing (ASPRS); LAZ is a loseless compressed version of LAS developed by Martin Isenburg ( The data are exclusively in geographic coordinates (either NAD83 or ITRF94). The data are referenced vertically to the ellipsoid (either GRS80 or ITRF94), allowing for the ability to apply the most up to date geoid model when transforming to orthometric heights.
Last Modified: 2013-02-20
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