Lidar-Derived Seamless Digital Elevation Model (DEM) Mosaic for Coastal Topography—Chandeleur Islands, Louisiana, 23-25 June 2016

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Frequently anticipated questions:

What does this data set describe?

Title:
Lidar-Derived Seamless Digital Elevation Model (DEM) Mosaic for Coastal Topography—Chandeleur Islands, Louisiana, 23-25 June 2016
Abstract:
A digital elevation model (DEM) mosaic was produced for the Chandeleur Islands, Louisiana, from remotely sensed, geographically referenced elevation measurements collected by Leading Edge Geomatics (LEG) using a Leica Chiroptera II Bathymetric and Topographic Sensor. Dewberry reports that the nominal pulse spacing for this project was 1 point every 0.7 meters. Dewberry used proprietary procedures to classify the LAS according to project specifications: 0-Never Classified, 1-Unclassified, 2-Ground (includes model key point bit for points identified as Model Key Point), 7-Low Noise, 17-Bridges, 18-High Noise, 40-Bathymetric point or submerged topography (includes model key point bit for points identified as Model Key Point), 41-Water Surface, and 42-Derived water surface.
Supplemental_Information:
Processed data products are used by the U.S. Geological Survey Coastal and Marine Geology Program (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, 20171023, Lidar-Derived Seamless Digital Elevation Model (DEM) Mosaic for Coastal Topography—Chandeleur Islands, Louisiana, 23-25 June 2016: U.S. Geological Survey Data Release doi:10.5066/F7G73CM4, U.S. Geological Survey, St. Petersburg, FL.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -88.94020022
    East_Bounding_Coordinate: -88.77838392
    North_Bounding_Coordinate: 30.08005926
    South_Bounding_Coordinate: 29.72610024
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 23-Jun-2016
    Ending_Date: 25-Jun-2016
    Currentness_Reference:
    ground condition
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: 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: 16
      Transverse_Mercator:
      Scale_Factor_at_Central_Meridian: 0.999600
      Longitude_of_Central_Meridian: -87.000000
      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 1.00000
      Ordinates (y-coordinates) are specified to the nearest 1.00000
      Planar coordinates are specified in meters
      The horizontal datum used is North American Datum of 1983 (2011).
      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 (GEOID12B)
      Altitude_Resolution: 0.01
      Altitude_Distance_Units: meters
      Altitude_Encoding_Method:
      Explicit elevation coordinate included with horizontal coordinates
  7. How does the data set describe geographic features?

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
    U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL
    Cartographer/Lidar Coordinator
    600 4th Street South
    St. Petersburg, FL
    USA

    727 502-8086 (voice)
    727 502-8182 (FAX)
    afredericks@usgs.gov
    Hours_of_Service: M-F, 8:00-4:00 ET

Why was the data set created?

The purpose of this project was to produce a highly detailed and accurate digital elevation map for the Chandeleur Islands, Louisiana for use as a management tool and to make these data available to natural-resource managers and research scientists. To ensure that SPCMSC data management protocols were followed, this survey was assigned a USGS field activity number (FAN), 16CNT01. Additional survey and data details are available at https://cmgds.marine.usgs.gov/fan_info.php?fan=16CNT01. USGS Contract: G16PC00020 Task Order Number: G16D00701

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: Jun-2016 (process 1 of 6)
    Dewberry reports that the data for the Chandeleur Islands project was acquired by Leading Edge Geomatics using a Leica Chiroptera II Bathymetric and Topographic lidar sensor. LEG delivered raw calibrated lidar data to Dewberry referenced to:
    Chandeleur Island: Horizontal Datum-NAD83 (2011) Projection-UTM Zone 16 North Horizontal Units-meters Vertical Datum-NAD83 (2011), ellipsoid Vertical Units-meters
    This dataset encompasses 109 1500 m x 1500 m tiles. Both green lidar data and near-infrared (NIR) lidar data were acquired.
    Leading Edge Geomatics acquired, calibrated and performed the refraction correction to the lidar data. Light travels at different speeds in air versus water and its direction of travel or angle is changed or refracted when entering the water column. The refraction correction process corrects for this difference by adjusting the depth (distance traveled) and horizontal position (change of angle/direction) of the lidar data acquired within water.
    The calibration process considered all errors inherent with the equipment including errors in global postioning system (GPS), inertial measurement unit (IMU), and sensor specific parameters. Adjustments were made to achieve a flight line to flight line data match (relative calibration) and subsequently adjusted to control for absolute accuracy. Process steps to achieve this are as follows: Rigorous lidar calibration: all sources of error such as the sensor's ranging and torsion parameters, atmospheric variables, GPS conditions, and IMU offsets were analyzed and removed to the highest level possible. This method addresses all errors, both vertical and horizontal in nature. Ranging, atmospheric variables, and GPS conditions affect the vertical position of the surface, whereas IMU offsets and torsion parameters affect the data horizontally. The horizontal accuracy is proven through repeatability: when the position of features remains constant no matter what direction the plane was flying and no matter where the feature is positioned within the swath, relative horizontal accuracy is achieved. Absolute horizontal accuracy is achieved through the use of differential GPS with base lines shorter than 25 miles. The base station is set at a temporary monument that is 'tied-in' to the Continuously Operating Reference Station (CORS) network. The same position is used for every lift, ensuring that any errors in its position will affect all data equally and can therefore be removed equally.
    Vertical accuracy is achieved through the adjustment to ground control survey points within the finished product. Although the base station has absolute vertical accuracy, adjustments to sensor parameters introduces vertical error that must be normalized in the final (mean) adjustment. No control was collected by LEG for the two areas.
    The withheld and overlap bits are set and all headers, appropriate point data records, and variable length records, including spatial reference information, are updated in GeoCue software and then verified using proprietary Dewberry tools. Person who carried out this activity:
    Dewberry
    1000 N. Ashley Drive, Suite 801
    Tampa, FL
    USA

    813-225-1325 (voice)
    Hours_of_Service:
    Monday through Friday 9:00 AM to 5:00 PM (Eastern Standard Time)
    Date: Sep-2016 (process 2 of 6)
    Dewberry reports that they utilize a variety of software suites for inventory management, classification, and data processing. All lidar related processes begin by importing the data into the GeoCue task management software. The swath data are tiled according to project specifications (1500 m x 1500 m). The tiled data are then opened in Terrascan where Dewberry classifies problematic edge of flight line points that are geometrically unusable with the withheld bit. These points are separated from the main point cloud so that they are not used in the ground algorithms. Overage points are then identified with the overlap bit.
    Dewberry used ArcGIS to create 2-D breaklines. These breaklines defined land/water interfaces and were used in conjunction with the ground algorithms to define topographic (class 2) and bathymetric bottom (40). Dewberry then uses an intelligently thinned ground classification to identify model key points, which are flagged with the Model Key Point bit for both class 2 and class 40.
    Dewberry then applies a proprietary ground classification routines to remove any non-ground points and generate an accurate ground/bathymetric surface. As part of the ground routine, low noise points are classified to class 7 and high noise points are classified to class 18. Water surface points are classified to class 41, also Derived Water Surface class 42 is classed and flagged as synthetic. Once the ground routine has been completed, bridge decks are classified to class 17 using bridge breaklines compiled by Dewberry. A manual quality control (QC) routine is then performed using hillshades, cross-sections, and profiles within the Terrasolid software suite. After this QC step, a peer review is performed on all tiles and a supervisor's manual inspection is completed on a percentage of the classified tiles based on the project size and variability of the terrain.
    A final QC is performed on the data. All headers, appropriate point data records, and variable length records, including spatial reference information, are updated in GeoCue software and then verified using proprietary Dewberry tools.

    The data were classified as follows: Class 1 = Unclassified. This class includes vegetation, buildings, noise etc. Class 2 = Ground (includes model key point bit for points identified as Model Key Point) Class 7 = Low Noise Class 17 = Bridge Decks Class 18 = High Noise Class 40 = Bathymetric Point (includes model key point bit for points identified as Model Key Point) Class 41 = Water Surface Class 42 = Derived Water Surface
    The LAS header information was verified to contain the following: Class (Integer) Adjusted GPS Time (0.0001 seconds) Easting (0.003 m) Northing (0.003 m) Elevation (0.003 m) Echo Number (Integer) Echo (Integer) Intensity (16-bit integer) Flight Line (Integer) Scan Angle (degree) Dewberry used GeoCue software to convert the source lidar to orthometric Geoid 12B. This dataset was used to create the other orthometric deliverables. Spatial reference information is updated in GeoCue software and then verified using proprietary Dewberry tools. Dewberry used GeoCue software to produce intensity imagery from the source lidar. The intensity imagery is georeferenced ortho-imagery that spatially aligns with the source lidar. The intensity imagery is created from the full point cloud first returns to show the full representation of the lidar dataset and was created with a 0.3-meter pixel resolution. The final format of the imagery is 8-bit, unsigned integer, grayscale GeoTIFF. Person who carried out this activity:
    Dewberry
    1000 N. Ashley Drive, Suite 801
    Tampa, FL
    USA

    813-225-1325 (voice)
    Hours_of_Service:
    Monday through Friday 9:00 AM to 5:00 PM (Eastern Standard Time)
    Date: Dec-2016 (process 3 of 6)
    Dewberry reports that the void polygon layer was created in Global Mapper where every bathy bottom point was used to create a grid. The distance or threshold that sets how far Global Mapper can interpolate around each bathy bottom point was set as 2. The higher the interpolation threshold, the more bathy bottom points are connected to create a continuous surface in the Global Mapper grid with fewer areas of NoData. The NoData areas in the Global Mapper grids are exported to polygons. Void polygons greater than 9 square meters are imported into Esri ArcGIS geodatabases, where they are incorporated into the terrains as soft erase features. When the terrains are exported to raster, the void polygons used as an erase in the terrain remain as areas of NoData. The final void polygon layer was created using the final lidar dataset, after all editing, review, and corrections were performed. Person who carried out this activity:
    Dewberry
    1000 N. Ashley Drive, Suite 801
    Tampa, FL
    USA

    813-225-1325 (voice)
    Hours_of_Service:
    Monday through Friday 9:00 AM to 5:00 PM (Eastern Standard Time)
    Date: Jan-2017 (process 4 of 6)
    Dewberry reports that class 2, ground, and class 40, bathymetric point, lidar points are exported from the LAS files into an ArcCatalog Geodatabase (GDB) in multipoint format. The final void polygons are imported into the same GDB and an Esri Terrain dataset is generated from these inputs. The surface type of each input is as follows: Ground/Bathymetric Multipoint: Masspoints; Void Polygons: Soft Erase. The Esri Terrain is converted to a raster. The raster is created using linear interpolation with a 1 meter cell size. The DEM is reviewed with hillshades in both ArcGIS and Global Mapper. Hillshades allow the analyst to view the DEMs in 3D and to more efficiently locate and identify potential issues. Analysts review the DEM for missed lidar classification issues, anomalies, issues with the void polygons/NoData areas, and artifacts that are introduced during the raster creation process.The corrected and final DEM is clipped to individual tiles. Dewberry uses a proprietary tool that clips the DEM to each tile located within the final tile grid, names the clipped DEM to the tile grid Cell name, and verifies that final extents are correct. All individual tiles are loaded into Global Mapper for the last review. During this last review, an analyst checks to ensure full, complete coverage, no issues along tile boundaries, tiles seamlessly edge-match, and that there are no remaining processing artifacts in the dataset. Person who carried out this activity:
    Dewberry
    1000 N. Ashley Drive, Suite 801
    Tampa, FL
    USA

    813-225-1325 (voice)
    Hours_of_Service:
    Monday through Friday 9:00 AM to 5:00 PM (Eastern Standard Time)
    Date: 30-Jun-2016 (process 5 of 6)
    The provided tiled DEM .tif files were mosaicked using Global Mapper 16.1 (20160309) and exported as one GeoTIFF. Person who carried out this activity:
    Xan Fredericks
    U.S. Geological Survey, U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL
    Cartographer/lidar Coordinator
    600 4th Street South
    St. Petersburg, FL
    USA

    727 502-8086 (voice)
    afredericks@usgs.gov
    Hours_of_Service: M-F, 8:00-4:00 ET
    Date: 13-Oct-2020 (process 6 of 6)
    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?

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

  1. How well have the observations been checked?
  2. How accurate are the geographic locations?
    Dewberry reports that the DEMs are derived from the source lidar and that horizontal accuracy is not performed on the DEMs. Only checkpoints photo-identifiable in the intensity imagery can be used to test the horizontal accuracy of the lidar. Photo-identifiable checkpoints in intensity imagery typically include checkpoints located at the ends of paint stripes on concrete or asphalt surfaces or checkpoints located at 90-degree corners of different reflectivity, for example, a sidewalk corner adjoining a grass surface. The XY coordinates of checkpoints, as defined in the intensity imagery, are compared to surveyed XY coordinates for each photo-identifiable checkpoint. These differences are used to compute the tested horizontal accuracy of the lidar. As not all projects contain photo-identifiable checkpoints, the horizontal accuracy of the lidar cannot always be tested.
  3. How accurate are the heights or depths?
    Dewberry reports that the DEMs are derived from the source lidar. The DEMs are created using controlled and tested methods to limit the amount of error introduced during DEM production so that any differences identified between the source lidar and final DEMs can be attributed to interpolation differences. DEMs are created by averaging several lidar points within each pixel, which may result in slightly different elevation values at a given location when compared to the source LAS. Elevation variations are tested by comparing survey checkpoints to a triangulated irregular network (TIN) that is created from the lidar ground and submerged bottom points. TINs do not average several lidar points together but interpolate (linearly) between two or three points to derive an elevation value. The vertical accuracy requirements of this task order for non-vegetated vertical accuracy (NVA) of the DEMs are 10 cm RMSEz and <= 19.6 cm at the 95% confidence. The vertical accuracy is 11.1 cm RMSEz and 21.7 cm at the 95% confidence level for non-vegetated data, which do not meet the task order requirements. However, the result of 21.4 cm at the 95th percentile for vegetated vertical accuracy (VVA) data does meet the requirement of <= 29.4 cm at the 95th percentile.
  4. Where are the gaps in the data? What is missing?
    Dewberry reports that data covers the project boundary to the fullest extent possible depending on water clarity, environmental conditions, and sensor signal returns.
  5. How consistent are the relationships among the observations, including topology?
    Dewberry reports that data cover the project boundary. "NoData" values correspond with lack of submerged and/or bare-earth data within the survey bounds.

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:
Public domain data from the U.S. Government are freely redistributable with proper metadata and source attribution. 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
    Cartographer/Lidar Coordinator, U.S. Geological Survey
    600 4th Street South
    St. Petersburg, FL
    USA

    727 502-8086 (voice)
    Hours_of_Service: M-F, 8:00-4:00 ET
  2. What's the catalog number I need to order this data set? CHAN2016_SM_z16_n88g12B_mosaic.tif
  3. What legal disclaimers am I supposed to read?
    Although these data have been processed successfully on a computer system at the 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 and/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?
  5. Is there some other way to get the data?
    Contact U.S. Geological Survey for details.

Who wrote the metadata?

Dates:
Last modified: 02-Nov-2020
Metadata author:
Xan Fredericks
U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL
Cartographer/Lidar Coordinator
600 4th Street South
St. Petersburg, FL
USA

727 502-8086 (voice)
afredericks@usgs.gov
Hours_of_Service: M-F, 8:00-4:00 ET
Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
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