Digital elevation model (DEM) of Looe Key, Florida, 2021

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?
   Hatcher, Gerald A., Kranenburg, Christine J., and Warrick, Jonathan A., 20221005, Digital elevation model (DEM) of Looe Key, Florida, 2021: data release DOI:10.5066/P9WSF09G, U.S. Geological Survey - Pacific Coastal and Marine Science Center, Santa Cruz, California.

   Online Links:

   • https://doi.org/10.5066/P9WSF09G

   This is part of the following larger work.
   Hatcher, Gerald A., Kranenburg, Christine J., Warrick, Jonathan A., Bosse, Stephen T., Zawada, David G., Yates, Kimberly K., and Johnson, Selena A., 2022, Overlapping seabed images and location data acquired using the SQUID-5 system at Looe Key, Florida, in July 2021, with derived point cloud, digital elevation model and orthomosaic of submerged topography: data release DOI:10.5066/P9WSF09G, U.S. Geological Survey - Pacific Coastal and Marine Science Center, Santa Cruz, California.

   Online Links:

   • https://doi.org/10.5066/P9WSF09G

2. What geographic area does the data set cover?

   West_Bounding_Coordinate: -81.4089893
   East_Bounding_Coordinate: -81.4019610
   North_Bounding_Coordinate: 24.5473158
   South_Bounding_Coordinate: 24.5445037
   

3. What does it look like?

   DEM_example.jpg (JPEG)

   Full-resolution sample view of the DEM.

4. Does the data set describe conditions during a particular time period?

   Beginning_Date: 15-Jul-2021

   Ending_Date: 19-Jul-2021

   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?
      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: 17N
      Transverse_Mercator:

      Scale_Factor_at_Central_Meridian: 0.9996
      Longitude_of_Central_Meridian: -81
      Latitude_of_Projection_Origin: 0.0
      False_Easting: 500000.0
      False_Northing: 0.0
      

      Planar coordinates are encoded using coordinate pair
      Abscissae (x-coordinates) are specified to the nearest 0.01
      Ordinates (y-coordinates) are specified to the nearest 0.01
      Planar coordinates are specified in Meters
      The horizontal datum used is North American Datum of 1983 (2011).
      The ellipsoid used is GRS 1980.
      The semi-major axis of the ellipsoid used is 6378137.000000.
      The flattening of the ellipsoid used is 1/298.257222101.
      

      Vertical_Coordinate_System_Definition:

      Altitude_System_Definition:

      Altitude_Datum_Name: North American Vertical Datum 1988 (NAVD88)
      Altitude_Resolution: 0.001
      Altitude_Distance_Units: meters
      Altitude_Encoding_Method: Attribute values
      

7. How does the data set describe geographic features?

   Entity_and_Attribute_Overview:

   The DEM is presented as a 32-bit floating point GeoTIFF where pixels represent elevation in meters relative to NAVD88 and the no-data value is -32767. The horizontal projection is NAD83(2011) UTM Zone 17N.

   Entity_and_Attribute_Detail_Citation: U.S. Geological Survey
   

Who produced the data set?

1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
   • Gerald A. Hatcher
   • Christine J. Kranenburg
   • Jonathan A. Warrick
2. Who also contributed to the data set?
   Data collection was funded by the U.S. Geological Survey Pacific Coastal Marine Science Center and the U.S. Geological Survey Saint Petersburg Coastal and Marine Science Center. The authors would like to thank Dr. Jason Spadaro, Assistant Professor, Marine Science and Technology, College of the Florida Keys for installing calibration targets on the reef, Lisa Symons, Regional Response Coordinator, and the staff of the Eastern Region, Office of National Marine Sanctuaries, NOAA Florida Keys National Marine Sanctuary, for coordination efforts.
3. To whom should users address questions about the data?
   U.S. Geological Survey, Pacific Coastal and Marine Science Center

   Attn: PCMSC Science Data Coordinator

   2885 Mission Street

   Santa Cruz, CA
   

   831-460-4747 (voice)

   pcmsc_data@usgs.gov

Why was the data set created?

How was the data set created?

1. From what previous works were the data drawn?

   raw images (source 1 of 2)

   Hatcher, Gerald A., Kranenburg, Christine J., Warrick, Jonathan A., Bosse, Stephen T., Zawada, David G., Yates, Kimberly K., and Johnson, Selena A., 2022, Overlapping seabed images collected at Looe Key, Florida, 2021: U.S. Geological Survey - Pacific Coastal and Marine Science Center, online.

   Online Links:

   • https://doi.org/10.5066/P9WSF09G

   Type_of_Source_Media: digital images
   Source_Contribution:

   raw images to which Structure-from-Motion (SfM) techniques were applied

   GNSS antenna positions (source 2 of 2)

   Hatcher, Gerald A., Kranenburg, Christine J., Warrick, Jonathan A., Bosse, Stephen T., Zawada, David G., Yates, Kimberly K., and Johnson, Selena A., 2022, GNSS locations of seabed images collected at Looe Key, Florida, 2021: U.S. Geological Survey - Pacific Coastal and Marine Science Center, online.

   Online Links:

   • https://doi.org/10.5066/P9WSF09G

   Type_of_Source_Media: ASCII file
   Source_Contribution:

   Location data for the raw images to which Structure-from-Motion (SfM) techniques were applied

2. How were the data generated, processed, and modified?

   Date: 01-Dec-2021 (process 1 of 3)

   IMAGERY COLOR CORRECTION Because of the strong color modifications caused by light adsorption and scattering in underwater imaging, a color correction process was conducted on the raw images. The color correction was a twofold process. First, images were corrected for the high adsorption (and low color values) in the red band using the color balancing techniques of Ancuti and others (2017). For this, the red channel was modified using the color compensation equations of Ancuti and others (2017, see equation 4 on page 383) that use both image-wide and pixel-by-pixel comparisons of red brightness with respect to green brightness. After compensation, the images were white balanced using the "greyworld" assumption that is summarized in Ancuti and others (2017). Combined, these techniques ensured that each color band histogram was centered on similar values and had similar spread of values. The remaining techniques of Ancuti and others (2017), which include sharpening techniques and a multi-product fusion, were not employed. The resulting images utilized only about a quarter to a half of the complete 0-255 dynamic range of the three-color bands. Thus, the brightness values of each band were stretched linearly over the complete range while allowing the brightest and darkest 0.05 percent of the original image pixels (that is, 2506 of the 5.013 million pixels) to be excluded from the histogram stretch. This final element was included to ensure that light or dark spots in the images, which often occurred from water column particles or image noise, did not exert undo control on the final brightness values. Color-corrected images were output with the same file names and file types as the originals to make replacement within the SfM photogrammetry project easy. As a courtesy, the script used to implement this procedure is provided as a supplemental support file (OrthoImage_Color_Correction_Procedure.m), included with this data release. Person who carried out this activity:
   

   Jonathan A. Warrick

   U.S. Geological Survey, Pacific Coastal and Marine Science Center

   Research Geologist

   2885 Mission St.

   Santa Cruz, CA
   

   USA

   831-460-7569 (voice)

   jwarrick@usgs.gov

   Data sources used in this process:

   • raw images

   Data sources produced in this process:

   • color-corrected images

   Date: 10-Dec-2021 (process 2 of 3)

   SfM PHOTOGRAMMETRY Digital imagery and position data recorded by the SQUID-5 system were processed using Structure-from-Motion (SfM) photogrammetry techniques that generally follow the workflow outlined by Hatcher and others (2020). These techniques are detailed here and include specific references to parameter settings and processing workflow. The primary software used for SfM processing was Agisoft Metashape Professional, version 1.6.6, build 11715, which will be referred to as "Metashape" in the discussion herein. Because of the large number of images in this dataset, processing was conducted on a 792-CPU-core linux-based High-Performance Computing (HPC) cluster at the USGS Advanced Research Computing (ARC) group (https://doi.org/10.5066/P9XE7ROJ). First, the raw images collected during the six mission days were added to a new project in Metashape. Raw images were used over the color-corrected images, owing to their larger dynamic range, which generally resulted in more SfM tie points. The images were derived from only four of the five cameras on the SQUID-5 system due to a camera focusing problem (see metadata for the raw image files for more explanation), so each camera was assigned a unique camera calibration group in the Camera Calibration settings. Within the Camera Calibration settings, the camera parameters were also entered as 0.00345 x 0.00345 mm pixel sizes for all camera sensors, 8 mm focal length for the central camera (CAM13), and 6 mm focal lengths for the remaining cameras (CAM39, CAM75, CAM82). These different focal lengths represented different lenses chosen for each camera. Additionally, the cameras required offsets to transform the GNSS positions to each camera's entrance pupil (that is, optical center). Initial measurements of these offsets were obtained using a separate SfM technique, outlined in Hatcher and others (2020), which found the offsets to be: Camera X(m) Y(m) Z(m) CAM13 0.034 0.011 0.840 CAM39 0.273 -0.109 0.916 CAM75 0.131 0.559 0.754 CAM82 -0.010 -0.594 0.762 Where X and Y are the camera sensor parallel offsets, and Z is the sensor normal offset. The accuracy settings were chosen to be 0.01 m for CAM13 and 0.025 m for the other 3 cameras. Lastly, these offsets were allowed to be adjusted using the "Adjust GPS/INS offset" option, because slight camera shifts may occur with each rebuild and use of the SQUID-5 system. The SQUID-5 GNSS antenna positions were then imported into the project and matched with each image by time. The easting and northing (in meters) were obtained from the NAD83 UTM Zone 17N data, and altitudes were obtained from the NAVD88 orthometric heights (in meters). Prior to aligning the data, the Metashape reference settings were assigned. The coordinate system was "NAD83(2011) / UTM zone 17N" The camera accuracy was 0.10 m in the horizontal dimensions and 0.15 m in the vertical, following an examination of the source GNSS data. Tie point accuracy was set at 1.0 pixels. The remaining reference settings were not relevant, because there were no camera orientation measurements, marker points, or scale bars in the SfM project. The data were then aligned in Metashape using the "Align Photos" workflow tool. Settings for the alignment included "High" accuracy and "Reference" preselection using the "Source" information. This latter setting allowed the camera position information to assist with the alignment process. Additionally, the key point limit was set to 50,000 and the tie point limit was assigned a value of zero, which allows for the generation of the maximum number of points for each image. Lastly, neither the "Guided image matching" nor the "Adaptive camera model fitting" options were used. This process resulted in over 112 million tie points. The total positional errors for the cameras were reported to be 0.017 m, 0.018 m, and 0.048 m in the east, north and altitude directions, respectively. Thus, the total positional error was 0.054 m. To improve upon the camera calibration parameters and computed camera positions, an optimization process was conducted that was consistent with the techniques of Hatcher and others (2020), which are based on the general principles provided in Over and others (2021). First, a duplicate of the aligned data was created in case the optimization process eliminated too much data using the "Duplicate Chunk" tool. Within the new chunk, the least valid tie points were removed using the "Gradual Selection" tools. As noted in Hatcher and others (2020), these tools are used less aggressively for the underwater imagery of SQUID-5 than commonly used for aerial imagery owing to the differences in image quality. First, all points with a "Reconstruction Uncertainty" greater than 20 were selected and deleted. Then, all points with a "Projection Accuracy" greater than 8 were selected and deleted. The camera parameters were then recalibrated with the "Optimize Cameras" tool. Throughout this process the only camera parameters that were adjusted were f, k1, k2, k3, cx, cy, p1, and p2. Once the camera parameters were adjusted, all points with "Reprojection Errors" greater than 0.4 were deleted, and the "Optimize Cameras" tool was used one final time. This optimization process resulted in slightly over 59.3 million tie points, a reduction of roughly 47 percent of the original tie points. The camera positional errors were reported to be 0.015 m, 0.015 m, and 0.047 m in the east, north and altitude directions, respectively, and the total positional error was 0.052 m. The final computed arm offsets were found to be: Camera X(m) Y(m) Z(m) CAM13 0.028 0.016 0.821 CAM39 0.274 -0.106 0.912 CAM75 0.128 0.562 0.741 CAM82 -0.015 -0.570 0.765 Following the alignment and optimization of the SQUID-5 data, mapped SfM products were generated in Metashape. For these steps, the original raw images were replaced with color-corrected images. This replacement was conducted by resetting each image path from the raw image to the color-corrected image. First, a three-dimensional dense point cloud was generated using the "Build Dense Cloud" workflow tool. This was run with the "High" quality setting and the "Moderate" depth filtering, and the tool was set to calculate both point colors and confidence. The resulting dense cloud was over 5 billion points over the 0.07 square kilometer survey area, or roughly 68,000 points per square meter (6.8 points per square centimeter). The dense points were classified by thresholding Metashape-computed confidence values, which are equivalent to the number of image depth maps that were integrated to make each point. Values of one were assigned "low noise", and values of two and greater were assigned "unclassified". The final Dense cloud was partitioned into blocks (also referred to as tiles) measuring 150 meters on a side, and exported with point colors and classification as a LAZ file type. Person who carried out this activity:
   

   Christine J. Kranenburg

   U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center

   Cartographer

   600 4th Street South

   St. Petersburg, FL
   

   USA

   727-502-8000 (voice)

   ckranenburg@usgs.gov

   Data sources used in this process:

   • raw images
   • color-corrected images
   • GNSS antenna positions

   Data sources produced in this process:

   • point cloud

   Date: 04-Mar-2022 (process 3 of 3)

   GENERATION OF DIGITAL ELEVATION MODEL (DEM) A digital elevation model (DEM), which is a x,y raster of elevation values, was generated from the point cloud using the Metashape "Build DEM" workflow tool using a geographic projection, dense cloud source data, disabled interpolation, and the recommended output resolution of 0.00627 meters. The DEM was partitioned into 150-meter blocks and resampled to a 1-cm resolution pixel size during export. DEM tile boundaries are coincident with those of the point cloud. Person who carried out this activity:
   

   Christine J. Kranenburg

   U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center

   Cartographer

   600 4th Street South

   St. Petersburg, FL
   

   USA

   727-502-8000 (voice)

   ckranenburg@usgs.gov

   Data sources used in this process:

   • point cloud

   Data sources produced in this process:

   • DEM

3. What similar or related data should the user be aware of?
   Hatcher, Gerald A., Warrick, Jonathan A., Ritchie, Andrew C., Dailey, Evan T., Zawada, David G., Kranenburg, Christine, and Yates, Kimberly K., 2020, Accurate bathymetric maps from underwater digital imagery without ground control.

   Online Links:

   • https://doi.org/10.3389/fmars.2020.00525

   Other_Citation_Details:

   Hatcher, G.A., Warrick, J.A., Ritchie, A.C., Dailey, E.T., Zawada, D.G., Kranenburg, C., and Yates, K.K., 2020, Accurate bathymetric maps from underwater digital imagery without ground control: Frontiers in Marine Science, v. 7, art. 525, doi:10.3389/fmars.2020.00525

   Ancuti, Codruta O., Ancuti, Cosmin, Vleeschouwer, Christophe De, and Bekaert, Philippe, 2017, Color balance and fusion for underwater image enhancement.

   Online Links:

   • https://doi.org/10.1109/TIP.2017.2759252

   Other_Citation_Details:

   Ancuti, C.O., Ancuti, C., De Vleeschouwer, C., and Bekaert, P., 2017, Color balance and fusion for underwater image enhancement: IEEE Transactions on Image Processing, v. 27, p. 379-393, doi:10.1109/TIP.2017.2759252

   Over, Jin-Si R., Ritchie, Andrew C., Kranenburg, Christine J., Brown, Jenna A., Buscombe, Daniel, Noble, Tom, Sherwood, Christopher R., Warrick, Jonathan A., and Wernette, Philippe A., 2021, Processing Coastal Imagery with Agisoft Metashape Professional Edition, Version 1.6--Structure from Motion Workflow Documentation: U.S. Geological Survey Open-File Report 2021-1039.

   Online Links:

   • https://doi.org/10.3133/ofr20211039

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

1. How well have the observations been checked?
   The accuracy of the position data used for SfM data processing is based on the accuracy of the post-processed GNSS navigation data, which produced a 10-Hz vehicle trajectory with an estimated 2-sigma accuracy of 10 cm horizontal and 15 cm vertical. The horizontal and vertical accuracies of the surface models generated by SfM were assessed with positional error assessments of the cameras and found to be less than 3 cm in the horizontal dimensions and less than 5 cm in the vertical.
2. How accurate are the geographic locations?
   Previous SfM-based measurements of the field-based Sediment Elevation Table (SET) stations at USGS field sites in the Florida Keys were within 3 cm of the total uncertainty of the field-based GPS measurements. Additionally, the average horizontal scaling of the models was found to be between 0.016 percent and 0.024 percent of water depth. No independent assessment of horizontal accuracy was possible from the Looe Key field site.
3. How accurate are the heights or depths?
   Previous SfM-based measurements of the field-based Sediment Elevation Table (SET) stations at USGS field sites in the Florida Keys were within 3 cm of the total uncertainty of the field-based GPS measurements. The average vertical scaling of the models is between 0.016 percent and 0.024 percent of water depth. No independent assessment of vertical accuracy was possible from the Looe Key field site.
4. Where are the gaps in the data? What is missing?
   Dataset is considered complete for the information presented, as described in the abstract. No data were collected in 2 of the 10 potential tiles covered by the 5-by-2 index map. Data in those tiles were either too deep to be captured with an optical system or too shallow to access with the vessel used during data collection. Users are advised to read the rest of the metadata record carefully for additional details.
5. How consistent are the relationships among the observations, including topology?
   Five submerged marker buoys are present and visible in the data products. These buoys are anchored to the seafloor with ropes and resemble sea mounts in the DEM. They are approximately 5 meters tall, less than 1 meter in diameter and are located at or near the following coordinates: Easting(m) Northing(m) 459185.5, 2714832.4 458998.4, 2714711.2 458608.7, 2714590.1 458720.3, 2714628.0 458787.1, 2714697.5

How can someone get a copy of the data set?

1. Who distributes the data set? (Distributor 1 of 1)
   
   U.S. Geological Survey - CMGDS

   2885 Mission Street

   Santa Cruz, CA
   

   1-831-427-4747 (voice)

   pcmsc_data@usgs.gov
2. What's the catalog number I need to order this data set? The DEM GeoTIFF is available in 1-cm resolution.
3. What legal disclaimers am I supposed to read?
   Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by 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.
4. How can I download or order the data?
   • Availability in digital form:

     Data format:	Eight individual compressed GeoTIFF files available for download range in size from 52 MB to 686 MB. in format GeoTIFF Size: 3415
     Network links:	https://doi.org/10.5066/P9WSF09G

   • Cost to order the data: none

Who wrote the metadata?

Dates:

Last modified: 05-Oct-2022

Metadata author:

U.S. Geological Survey, Pacific Coastal and Marine Science Center

Attn: PCMSC Science Data Coordinator

2885 Mission Street

Santa Cruz, CA

831-460-4747 (voice)

pcmsc_data@usgs.gov

Metadata standard:

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