KEYS2016_SM_z17_n88g12B_mosaic_metadata: Coastal Topography-Upper Florida Keys Reef Tract, Florida, 26-30 June 2016

Frequently anticipated questions:

• What does this data set describe?
  1. How might this data set be cited?
  2. What geographic area does the data set cover?
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
  5. What is the general form of this data set?
  6. How does the data set represent geographic features?
  7. How does the data set describe geographic features?
• Who produced the data set?
  1. Who are the originators of the data set?
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
• Why was the data set created?
• How was the data set created?
  1. From what previous works were the data drawn?
  2. How were the data generated, processed, and modified?
  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?
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
  5. How consistent are the relationships among the data, including topology?
• How can someone get a copy of the data set?
  1. Are there legal restrictions on access or use of the data?
  2. Who distributes the data?
  3. What's the catalog number I need to order this data set?
  4. What legal disclaimers am I supposed to read?
  5. How can I download or order the data?
• Who wrote the metadata?

What does this data set describe?

1. How might this data set be cited?
   U.S. Geological Survey, 20171226, KEYS2016_SM_z17_n88g12B_mosaic_metadata: Coastal Topography-Upper Florida Keys Reef Tract, Florida, 26-30 June 2016: U.S. Geological Survey Data Release doi:10.5066/F7QZ28XZ, U.S. Geological Survey, St. Petersburg, FL.

   Online Links:

   • https://doi.org/10.5066/F7QZ28XZ

2. What geographic area does the data set cover?

   West_Bounding_Coordinate: -80.4698
   East_Bounding_Coordinate: -80.1069
   North_Bounding_Coordinate: 25.4861
   South_Bounding_Coordinate: 25.0024
   

3. What does it look like?
4. Does the data set describe conditions during a particular time period?

   Beginning_Date: 26-Jun-2016

   Ending_Date: 30-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: 17
      Transverse_Mercator:

      Scale_Factor_at_Central_Meridian: 0.999600
      Longitude_of_Central_Meridian: -81.000000
      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

Why was the data set created?

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 data for the Florida Keys Reef Tract 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: Florida Keys: Horizontal Datum-NAD83 (2011 Projection-UTM Zone 17 North Horizontal Units-meters Vertical Datum-NAD83 (2011) ellipsoid Vertical Units-meters
   
   This dataset encompasses 184 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 positioning 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. The vertical accuracy of this lidar dataset was tested against sonar data. The result of the test was an 8-cm bias in the lidar data between the sonar and lidar. No adjustments to the data or derivative products were made based on these results.
   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)

   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 is tiled according to project specifications (1500 m x 1500 m). The tiled data is 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 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 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 and class 42 Derived Water Surface is set and flagged 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 lidar to the North American Datum of 1983 (NAD 83) (2011) 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 1-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)

   Date: Dec-2016 (process 3 of 6)

   Dewberry reports that the void polygon layer was created in Global Mapper where every bathymetry bottom point was used to create a grid. The distance or threshold that sets how far Global Mapper can interpolate around each bathymetry bottom point was set as 2. The higher the interpolation threshold, the more bathymetry 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 Arc 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)

   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 Arc Geodatabase (GDB) in multipoint format. The final void polygons are imported into the same GDB. An Esri Terrain is generated from these inputs. The surface type of each input is as follows: Ground/Bathymetric Multipoint: Masspoints and 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)

   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

   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 of these lidar and DEM datasets were not tested. The vertical accuracy of this lidar dataset was tested against sonar data. The result of the test was an 8c-m bias in the lidar data between the sonar and lidar. Independent assessment resulted in a 12-cm bias. No adjustments to the data or derivative products were made based on these results.
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?

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)
2. What's the catalog number I need to order this data set? KEYS2016_SM_z17_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?
   • Availability in digital form:

     Data format:	GeoTIFF (version 2) GeoTIFF
     Network links:	https://coastal.er.usgs.gov/data-release/doi-F7QZ28XZ/data/KEYS2016_SM_z17_n88g12B_mosaic.zip

   • Cost to order the data: None

Who wrote the metadata?

Dates:

Last modified: 28-Sep-2023

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

Metadata standard:

Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)