DS888-metadata: EAARL-B Coastal Topography—Fire Island, New York, pre-Hurricane Sandy, 2012: Seamless (Bare Earth and Submerged)

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What does this data set describe?

Title:
DS888-metadata: EAARL-B Coastal Topography—Fire Island, New York, pre-Hurricane Sandy, 2012: Seamless (Bare Earth and Submerged)
Abstract:
American Standard Code Information Interchange XYZ and binary point-cloud data, as well as a seamless (bare-earth and submerged) digital elevation model for part of Fire Island, New York, pre-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 5.24 centimeters for the bare earth topography. Additional data were insufficient to calculate an RMSE for the submerged topography. 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.
Supplemental_Information:
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, pre_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 Assessment 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.
  1. How might this data set be cited?
    U.S. Geological Survey, 2014, DS888-metadata: EAARL-B Coastal Topography—Fire Island, New York, pre-Hurricane Sandy, 2012: Seamless (Bare Earth and Submerged): U.S. Geological Survey Data Series 888, U.S. Geological Survey, St. Petersburg, FL.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -73.3684
    East_Bounding_Coordinate: -72.6776
    North_Bounding_Coordinate: 40.7906
    South_Bounding_Coordinate: 40.6023
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 27-Oct-2012
    Currentness_Reference:
    ground condition
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: tabular, vector, and raster digital data
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
      Indirect_Spatial_Reference: Tiling Index
      This is a Raster data set. It contains the following raster data types:
      • Dimensions, type Pixel
    2. What coordinate system is used to represent geographic features?
      Grid_Coordinate_System_Name: Universal Transverse Mercator
      Universal_Transverse_Mercator:
      UTM_Zone_Number: 18
      Transverse_Mercator:
      Scale_Factor_at_Central_Meridian: 0.999600
      Longitude_of_Central_Meridian: -75.000000
      Latitude_of_Projection_Origin: 0
      False_Easting: 500000.000000
      False_Northing: 0
      Planar coordinates are encoded using row and column
      Abscissae (x-coordinates) are specified to the nearest 2.500000
      Ordinates (y-coordinates) are specified to the nearest 2.500000
      Planar coordinates are specified in meters
      The horizontal datum used is North American Datum of 1983.
      The ellipsoid used is Geodetic Reference System 80.
      The semi-major axis of the ellipsoid used is 6378137.000000.
      The flattening of the ellipsoid used is 1/298.25722210100002.
      Vertical_Coordinate_System_Definition:
      Altitude_System_Definition:
      Altitude_Datum_Name: North American Vertical Datum of 1988
      Altitude_Resolution: 0.20
      Altitude_Distance_Units: meters
      Altitude_Encoding_Method:
      Explicit elevation coordinate included with horizontal coordinates
  7. How does the data set describe geographic features?
    *.xyz
    The "*" represents the file name. The file is .xyz ASCII space-delimited. (Source: Internally devised to maintain naming consistency.)
    X
    UTM easting in meters (Source: NAD83) varying value range
    Y
    UTM northing in meters (Source: NAD83) varying value range
    Z
    Altitude in meters (Source: NAVD88) varying value range
    Entity_and_Attribute_Overview:
    The input parameters for the random consensus filter (RCF) were: grid cell size (buffer) = 500 centimeters x 500 centimeters for bare earth and 1000 centimeters x 1000 centimeters for submerged topography; vertical tolerance (vertical width) = 60 centimeters for bare earth and 40 centimeters for submerged topography. Each pixel of the encoded GeoTIFF has an explicit elevation value associated with it. The GeoTIFF grid is encoded with the interpolated elevation value at a 2.5-meter resolution. The GeoTIFFs are created using Delauney triangulation, followed by linear interpolation based on the routines in the International Telephone and Telegraph Visual Information Solutions Interactive Data Language (IDL) code.
    Entity_and_Attribute_Detail_Citation: http://pubs.usgs.gov/of/2009/1078/

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • U.S. Geological Survey
  2. Who also contributed to the data set?
    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 is expected. 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 periods may be inaccurate because of 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.
  3. To whom should users address questions about the data?
    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
    600 4th Street South
    St. Petersburg, FL
    USA

    727 502-8086 (voice)
    727 502-8182 (FAX)
    afredericks@usgs.gov

Why was the data set created?

The purpose of this project was to produce highly detailed and accurate seamless digital elevation maps for part of Fire Island, New York, pre-Hurricane Sandy (October 2012 hurricane), for use as a management tool and to make these data available to natural-resource managers and research scientists.

How was the data set created?

  1. From what previous works were the data drawn?
  2. How were the data generated, processed, and modified?
    Date: 26-Mar-2014 (process 1 of 5)
    The data were collected using a Cessna 310 aircraft. The EAARL-B laser scanner collects the data using a green-wavelength (532-nanometer) raster scanning laser, while a digital camera acquires a visual record of the flight. The data are stored on hard drives and archived at the U.S. Geological Survey office in St. Petersburg, Florida. The navigational data are processed and then, along with the raw data, are downloaded into ALPS, or the Airborne Lidar Processing System (20121105–20140326). Data are converted from units of time to x,y,z points for elevation and formatted into .las and .xyz files, and the derived surface data are converted into raster data (GeoTIFFs). Person who carried out this activity:
    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
    600 4th Street South
    St. Petersburg, FL
    USA

    727 502-8086 (voice)
    afredericks@usgs.gov
    Date: 05-Sep-2014 (process 2 of 5)
    A bias correction of -16 centimeters (value determined from instrument calibrations) was applied to the point-cloud data using ALPS (20140905) to account for a change in configuration parameters. Data are formatted into .las and .xyz files, and the derived surface data are converted into raster data (GeoTIFFs). Person who carried out this activity:
    Christine Kranenburg
    Cherokee Nation Technology Solutions, U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL
    Programmer/Analyst
    600 4th Street South
    St. Petersburg, FL
    USA

    727 502-8129 (voice)
    ckranenburg@usgs.gov
    Date: 04-Apr-2014 (process 3 of 5)
    Metadata imported into ArcCatalog 10.1.1.3143 from XML file. Person who carried out this activity:
    Melanie Masessa
    Cherokee Nation Technology Solutions, U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL
    GIS Analyst
    600 4th Street South
    St. Petersburg, FL
    USA

    727 502-8096 (voice)
    mmasessa@usgs.gov
    Date: 24-Jan-2017 (process 4 of 5)
    Keywords section of metadata optimized for discovery in USGS Coastal and Marine Geology Data Catalog. Person who carried out this activity:
    U.S. Geological Survey
    Attn: Alan O. Allwardt
    Contractor -- Information Specialist
    2885 Mission Street
    Santa Cruz, CA

    831-460-7551 (voice)
    831-427-4748 (FAX)
    aallwardt@usgs.gov
    Date: 13-Oct-2020 (process 5 of 5)
    Added keywords section with USGS persistent identifier as theme keyword. Person who carried out this activity:
    U.S. Geological Survey
    Attn: VeeAnn A. Cross
    Marine Geologist
    384 Woods Hole Road
    Woods Hole, MA

    508-548-8700 x2251 (voice)
    508-457-2310 (FAX)
    vatnipp@usgs.gov
  3. What similar or related data should the user be aware of?
    Nayegandhi, A., Brock, J.C., and Wright, C.W., 2009, Small footprint, waveform-resolving lidar estimation of submerged and subcanopy topography in coastal environments: International Journal of Remote Sensing v. 30 no. 4, p. 861-878.


How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?
    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 5.24 centimeters RMSE for the bare earth topographic surface. Quality checks are built into the data-processing software.
  2. How accurate are the geographic locations?
    Raw elevation measurements have been determined to be within 1 meter in horizontal accuracy.
  3. How accurate are the heights or depths?
    Typical vertical elevation accuracies for these data are consistent with the point elevation data; however, a ground-control survey is not completed simultaneously with every lidar survey. Vertical accuracies may differ based on the type of terrain and the accuracy of the GPS and aircraft-attitude measurements.
  4. Where are the gaps in the data? What is missing?
    Several regions of the raster dataset are labeled as "No Data" in the GeoTIFF file. These "No Data" areas are a result of the survey not covering a particular region, optical water depth of greater than 1.5 Secchi disc depths, or the manual removal of lidar processing artifacts. The presence of "No Data" values does not necessarily indicate an absence of land, but rather an absence of survey coverage or the presence of prolific vegetation that the laser is not able to penetrate to return bare-earth data. This metadata file is generalized; each data file in this Data Series has its own corresponding metadata file.
  5. How consistent are the relationships among the observations, including topology?
    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, pre_e123_n4567_18).

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints None
Use_Constraints The U.S. Geological Survey requests to be acknowledged as originator of these data in future products or derivative research.
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey
    Attn: Xan Fredericks
    Lidar Validation and Processing Analyst, Cherokee Nation Technology Solutions
    600 4th Street South
    St. Petersburg, FL
    USA

    727 502-8086 (voice)
  2. What's the catalog number I need to order this data set? DS 888
  3. What legal disclaimers am I supposed to read?
    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 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.
  4. How can I download or order the data?
    • Availability in digital form:
      Data format: GeoTIFF (version 2) GeoTIFF
      Network links: https://doi.org/10.3133/ds888
    • Cost to order the data: None


Who wrote the metadata?

Dates:
Last modified: 10-Oct-2023
Metadata author:
Melanie Masessa
Cherokee Nation Technology Solutions, U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL
GIS Analyst
600 4th Street South
St. Petersburg, FL
USA

727 502-8096 (voice)
mmasessa@usgs.gov
Metadata standard:
FGDC Content Standards for Digital Geospatial Metadata (FGDC-STD-001-1998)

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