Laboratory Observations of Artificial Sand and Oil Agglomerates Video and Velocity Data: Sea Floor Interaction Experiment Interpretive Video Previews

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Frequently anticipated questions:


What does this data set describe?

Title:
Laboratory Observations of Artificial Sand and Oil Agglomerates Video and Velocity Data: Sea Floor Interaction Experiment Interpretive Video Previews
Abstract:
Weathered oil in the surf-zone after an oil spill may mix with suspended sediments to form sand and oil agglomerates (SOA). Sand and oil agglomerates may form in mats on the scale of tens of meters (m), and may break apart into pieces between 1 and 10 centimeters (cm) in diameter. These more mobile pieces are susceptible to alongshore and cross-shore transport, and lead to beach re-oiling on the time scale of months to years following a spill. The U.S. Geological Survey (USGS) conducted experiments March 10 - 13, 2014, to expand the available data on sand and oil agglomerate motion; test shear stress based incipient motion parameterizations in a controlled, laboratory setting; and directly observe SOA exhumation and burial processes. Artificial sand and oil agglomerates (aSOA) were created and deployed in a small-oscillatory flow tunnel in two sets of experiments, during which, video and velocity data were obtained. The first experiment, which was set up to help researchers investigate incipient motion, used with an immobile, rough bottom (referred to as false-floor) and the second–testing seafloor interactions–utilized with a coarse grain sand bottom (movable sand bed). Detailed information regarding the creation of the aSOA can be found in Dalyander et al. (2015). More information about the USGS laboratory experiment conducted in collaboration with the Naval Research Laboratory can be found in the associated Open File Report (OFR Number Unknown).
Supplemental_Information:
The zip file, 2017_309_DD_SFI_preview.zip, contains previews of interpretive video of movable bed, sea floor interaction, experiment video data with graphical representations of flow velocity collected during small-oscillatory flow tunnel laboratory experiments at the Naval Research Laboratory, Stennis Space Center, Stennis Mississippi. To ensure that SPCMSC data management protocols were followed, this survey was retroactively assigned a USGS field activity number (FAN), 2017-309-DD. Additional survey and data details are available at http://cmgds.marine.usgs.gov/fan_info.php?fan=2017-309-DD.
  1. How might this data set be cited?
    U.S. Geological Survey, 20170512, Laboratory Observations of Artificial Sand and Oil Agglomerates Video and Velocity Data: Sea Floor Interaction Experiment Interpretive Video Previews: U.S. Geological Survey Data Release doi:10.5066/F76D5R69, U.S. Geological Survey, Coastal and Marine Geology Program, Saint Petersburg, FL.

    Online Links:

    This is part of the following larger work.

    Jenkins, Robert L. III, Dalyander, P. Soupy, Penko, Allison M., and Long, Joseph W., 20180427, Laboratory Observations of Artificial Sand and Oil Agglomerates: Open-File Report 2018–1010, U.S. Geological Survey, Reston, VA.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -89.65100
    East_Bounding_Coordinate: -89.55700
    North_Bounding_Coordinate: 30.39500
    South_Bounding_Coordinate: 30.34500
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 10-Mar-2014
    Ending_Date: 13-Mar-2014
    Currentness_Reference:
    ground condition
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: video
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
    2. What coordinate system is used to represent geographic features?
  7. How does the data set describe geographic features?
    2017_309_DD_SFI_preview
    Previews of interpretive video product of sea floor interaction experiment video data with graphical representation of flow velocity. (Source: U.S. Geological Survey)
    Experiment Time (s)
    Vectrino velocity profiler record time of experiment segment. (Source: U.S. Geological Survey)
    Range of values
    Minimum:15
    Maximum:570
    Units:seconds
    Video Footage
    Video observations of experiment segment. (Source: U.S. Geological Survey) Recorded footage of the experiment (collected by two Canon 7D DSLR cameras) is included in each .mp4 file; the video is positioned above a graphical representation of the water velocity.
    Water Velocity (m/s)
    Smoothed, along-tank water velocity as measured by Vectrino velocity profiler during experiment segment. (Source: U.S. Geological Survey) Record of water velocity, which coincides with video record time period.
    Current Time in Video
    Indicates the instantaneous velocity which coincide with the current conditions presented in the video footage. (Source: U.S. Geological Survey) Indicates the instantaneous velocity which coincide with the current conditions presented in the video footage. This attribute does not represent video play-back time and may stop before the end of the video. This attribute, represented by a yellow dot, will not be present, momentarily, when velocity values are NaN. This attribute will also not be present once the velocity record ends if the last value is NaN.
    Entity_and_Attribute_Overview:
    The entity and attribute information provided here describes the data associated with the dataset. Please review the detailed descriptions that are provided (the individual attribute descriptions) for information on the values that appear as entries of the dataset.
    Entity_and_Attribute_Detail_Citation:
    The entity and attribute information was generated by the individual and/or agency identified as the originator of the dataset. Please review the rest of the metadata record for additional details and information.

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?
  3. To whom should users address questions about the data?
    P. Soupy Dalyander
    U.S. Geological Survey
    Research Oceanographer
    600 Fourth Street South
    Saint Petersburg, Florida
    USA

    727-502-8124 (voice)
    727-502-8001 (FAX)
    sdalyander@usgs.gov

Why was the data set created?

This dataset includes 20–58 second (s) preview video clips and velocity observations of artificial sand and oil agglomerates acquired with two Canon 7D DSLR cameras, collected during a 2014 USGS small-oscillatory flow tunnel experimentof sea floor interactions (SFI) that was conducted at the Naval Research Laboratory (NRL), Stennis Space Center, Mississippi. The information contained within these videos is also needed to capture exhumation and burial processes of artificial sand and oil agglomerates. Observed flow velocities, which provide additional information about aSOA incipient motion, were also collected during the sea floor interaction experiment (see 2017_309_DD_SFI_velocity.zip) also included in this data release.

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: 12-Mar-2014 (process 1 of 14)
    In March, 2014, experiments were conducted at NRL’s Sediment Dynamics Laboratory, located in Stennis, MS. Artificial sand-oil agglomerates were deployed in the small-oscillatory flow tunnel with a cross-sectional area of 25 cm by 25 cm, a test bed length of 2-m, and a 35-cm deep sediment well. Oscillating currents (simulating bottom velocities generated by waves) were driven in the tank by a flywheel with variable frequencies (20-90 rpm) and stroke lengths (22, 33, or 44 cm). For all experiments, the oscillatory current had a slight asymmetry resulting in preferential transport downstream (toward the sediment trap) in the tank. Two high-definition Canon 7D DSLR cameras were mounted outside of the tank to record movement, each with a unique, separate, field of view. Camera A was outfitted with an 18-55 mm zoom lens at a 29 mm focal length and Camera B used an 18 mm fisheye lens. The tank was also equipped with a Vectrino acoustic velocity profiler, mounted centrally. Additional information on the characteristics and design of the flow tunnel can be found in Calantoni and others (2013). Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 12-Mar-2014 (process 2 of 14)
    Initial Conditions for Experiment A, B, C, and D. Experiments A, B, and C were designed to capture burial, exhumation, and movement of individual aSOA over the range of size classes. Experiment D was designed to capture those processes for groups of aSOA of varying size.
    For experiment A, the movable sand bed was initially leveled. The aSOAs of diameter 0.5 cm, 1.0 cm, and 2.5 cm, were placed in order of class size in two rows. One row was placed proud (i.e. not partially buried) on the bottom, while the second row of aSOAs were placed partially buried with only the tops were exposed.
     The initial conditions of Experiment B were simply the final conditions of Experiment A. The bed was not leveled. The aSOAs ranging in diameter from 0.5 cm, 1 cm and 2.5cm were deployed sitting proud on the sand bed. A GoPro camera was also deployed in the trough of one bed ripple to provide a unique perspective of aSOA motion and sand bed evolution.
     The initial conditions of Experiment C utilized the final conditions of Experiment B. The bed was not re-leveled. The aSOAs ranging in diameter from 5 cm to 10 cm were deployed sitting proud on the sand bed. The GoPro camera was removed from the small-oscillatory flow tunnel.
     For experiment D, the movable sand bed was initially leveled. All previously deployed aSOA were removed. The aSOAs were deployed in two groupings which simulated recently broken up SOA mats. One grouping was arranged in a tight group, while the second was arranged loosely.
    
    The two Canon 7D DSLR cameras captured 1080p HD video at 30 frames per second of the proud and partially buried aSOAs. Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 12-Mar-2014 (process 3 of 14)
    The field of view of Camera A is over lapped by the field of view of Camera B. In the field of view of both Camera A and Camera B, is a small red LED indicator light, which signals the beginning of the Vectrino record for a given experiment segment for the purpose of syncing the Vectrino velocity profile data and video records in time. Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 12-Mar-2014 (process 4 of 14)
    Videos were captured by two HD Canon 7D DSLR cameras. Video recording was begun, manually, shortly after the flow tunnel fly-wheel motor was turned on. Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 12-Mar-2014 (process 5 of 14)
    Velocities were logged by a Vectrino acoustic Doppler velocity profiler mounted centrally within the tank. Velocity recording was started, manually, after the beginning of the video recording. The start of the velocity record was indicated in the video by a single blink of a red LED indicator light. The 3-dimensional (3D) velocity was logged by the Vectrino software package and saved as raw binary files with file extension ".ntk". The Vectrino acoustic velocity profiler measured 3D water velocity (m/s) of a 4 cm profile below the instrument and the distance from the instrument to the sand bed (m) using coherent Doppler processing, at a frequency of 100 Hertz (Hz). Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 12-Aug-2015 (process 6 of 14)
    Raw Vectrino data were processed in MATLAB 2015b by a script called “VectrinoII_ProcessData.m” (2011) (NRL script) which extracted time, depth information, and 3D velocity (m/s) from raw data files. Next, velocities were processed iteratively to remove spikes in the data.
    First, velocities were first passed through a MATLAB built-in one dimensional smoothing filter (filter.m) with a window size of ten.
    Second, the difference was taken between the raw and smoothed time series and the standard deviation of that difference was calculated.
    Third, points with a difference greater than three times the standard deviation were identified, and replaced with the smoothed signal value at the same time.
    The first, second, and third, steps were then repeated three times, with the previously de-spiked signal replacing the input each time, which produced final, quality controlled, de-spiked and smoothed de-spiked time series of velocities.
    
    De-spiked and smoothed de-spiked records of 3D velocity data, time, and depth information were re-saved in MATLAB readable ‘.mat’ files. De-spiked and smoothed de-spiked velocity data were treated with an additional quality control step.
    A measure of signal quality, called Correlation, was recorded by the Vectrino profiler along 	with the raw data. Correlation is the measure of the data correlation as returned by each of the three acoustic beams of the profiler.
    Time points with correlation less than 70% are replaced in the record with non-number (NaN) values.
    
    Quality controlled records of de-spiked and smoothed de-spiked velocity were saved in MATLAB readable ‘.mat’ files. Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 21-Aug-2015 (process 7 of 14)
    Raw video data were processed through MATLAB with a script called 'video2JPEG.m' (SPCMSC script), which utilizes MATLAB built-in function "VideoReader". Each frame of the raw video was read into MATLAB and re-saved as a unique, numbered and ordered JPEG image to form a series of JPEG images for each frame of the raw video. The series of JPEG images were then saved automatically by 'video2JPEG.m' to a unique directory named for the experiment segment. 'video2JPEG.m' also extracted and confirmed video framerate as 30 frames per second. Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 24-Sep-2015 (process 8 of 14)
    Time differences between video and corresponding velocity record is established by identifying the exact frame in which the Vectrino red LED indicator light blinks in the camera view. The time (in seconds) at which the Vectrino begins recording in the video record is calculated as the frame number divided by the video framerate in frames per second. The video time record is then synced to the Vectrino time to create a consistent time record for both records. Video data recorded before beginning of velocity collection was retained in this record. Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 24-Sep-2015 (process 9 of 14)
    Flow velocity input for the interpretive video product was generated by extracting the along-tank component of flow velocity from the processed Vectrino 3D flow record. Free stream velocity is taken as the 3rd bin (approximately 3 mm). Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 30-Sep-2015 (process 10 of 14)
    Video data input for the interpretive video data product was not trimmed or sub-selected. All available video data for the given sea floor interaction experiment segment is presented. Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 12-Feb-2016 (process 11 of 14)
    Interpretive video products were next created in MATLAB using the built-in functions “imread,” “figure,” “imshow,” “plot,” "getframe," and “subplot.” The following steps are carried out in a loop, which carries out frame-by-frame plotting of processed JPEG images, velocity , and indicator of current time in record.
    A single JPEG from the video record is read using 'imread.'
    The single JPEG is rotated 180 degrees, to correct the image orientation.
    The overall figure is created using “figure.”
    The single JPEG from the video record is plotted within the overall figure using “subplot,” and “imshow.”
    The graph of velocity, and indicator of current time was plotted using “subplot,” and “plot.”
    The current overall figure is collated as a video frame in a sequence of frames using MATLAB built-in function “getframe.”
    The interpretive video product “.avi” file, has one frame added to it using MATLAB built-in function “WriteVideo” to add the frame created using “getframe.”
    
    Due to desktop computer memory limitations and large video file sizes, the video creation process is carried out iteratively over a number of consecutive video parts each 42 seconds in duration. Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 16-Mar-2016 (process 12 of 14)
    The recombination of consecutive video parts into the interpretive video product and file size reduction were handed in a single step via free compression and video editing software “Avidemux” prior to saving the final file in '.mp4' format which is presented in this data release. Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 30-Nov-2016 (process 13 of 14)
    Preview clips for each of the interpretive videos were also created using “Avidemux.” Videos were loaded into the editing software and trimmed down to a clip, which showcased a preview of the video observations, 20 seconds to 58 seconds in duration. These preview clips were then compressed again to reduce the file size, and saved as an “.mp4” video file. Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 13-Oct-2020 (process 14 of 14)
    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?
    Calantoni, J., Landry, B. J., and Penko, A. M., 2013, Laboratory observations of sand ripple evolution using bimodal gran size distributions under asymmetric oscillatory flows: Journal of Coastal Research Special Issue No. 65, p. 1497-1502, Coastal Education and Research Foundation, Inc., Plymouth, United Kingdom.

    Online Links:

    Dalyander, P.S., Long, J.W., Plant, N.G., and Mclaughlin, M., 2015, Nearshore dynamics of artificial sand and oil agglomerates: Marine Pollution Bulletin v.96, p. 344-355, Elsevier, Ltd., Atlanta, GA, USA.

    Online Links:


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

  1. How well have the observations been checked?
    The two Canon 7D DSLR cameras used to observe the oscillatory flow tunnel captured high-definition (HD) video with 1080p resolution, at 30 frames per second. File sizes are generally between 500 MB and 4 GB on disc, depending on experiment duration. One camera (Camera A) was outfitted with an 18-55 mm zoom lens at 29 mm focal length while the other camera (Camera B) used an 18 mm fisheye lens.
  2. How accurate are the geographic locations?
    A formal accuracy assessment of the horizontal positional information in the dataset has not been conducted.
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
    Video data is included for all experiments, and experiment segments. This dataset is considered complete for the information presented, as described in the abstract section. 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?
    All bottom videos were acquired with the same two cameras described above. Both cameras were mounted outside of the oscillatory flow tunnel.

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. Please recognize the U.S. Geological Survey as the originator of the dataset.
  1. Who distributes the data set? (Distributor 1 of 1)
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, Florida
    USA

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
  2. What's the catalog number I need to order this data set? The zip file, 2017_309_DD_SFI_preview.zip, contains the following MP4 video files: Sea_Floor_20140312_001a_preview.mp4, Sea_Floor_20140312_001b_preview.mp4, Sea_Floor_20140312_002a_preview.mp4, Sea_Floor_20140312_002b_preview.mp4, Sea_Floor_20140312_003a_preview.mp4, Sea_Floor_20140312_003b_preview.mp4, Sea_Floor_20140312_004a_preview.mp4, Sea_Floor_20140312_004b_preview.mp4, Sea_Floor_20140312_005a_preview.mp4, Sea_Floor_20140312_005b_preview.mp4, Sea_Floor_20140312_006a_preview.mp4, Sea_Floor_20140312_006b_preview.mp4, Sea_Floor_20140312_007a_preview.mp4, Sea_Floor_20140312_007b_preview.mp4, Sea_Floor_20140313_001a_preview.mp4, Sea_Floor_20140313_001b_preview.mp4, Sea_Floor_20140313_002a_preview.mp4, Sea_Floor_20140313_002b_preview.mp4, Sea_Floor_20140313_003a_preview.mp4, Sea_Floor_20140313_003b_preview.mp4, Sea_Floor_20140313_004a_preview.mp4, Sea_Floor_20140313_004b_preview.mp4, Sea_Floor_20140313_005a_preview.mp4, Sea_Floor_20140313_005b_preview.mp4, Sea_Floor_20140313_006a_preview.mp4, Sea_Floor_20140313_006b_preview.mp4, Sea_Floor_20140313_007a_preview.mp4, Sea_Floor_20140313_007b_preview.mp4, Sea_Floor_20140313_008a_preview.mp4, Sea_Floor_20140313_008b_preview.mp4, Sea_Floor_20140313_009a_preview.mp4, Sea_Floor_20140313_009b_preview.mp4
  3. What legal disclaimers am I supposed to read?
    This digital publication was prepared by an agency of the United States Government. Although these data have been processed successfully on a computer system at the U.S. Geological Survey, no warranty expressed or implied is made regarding the display or utility of the data on any other system, nor shall the act of distribution imply any such warranty. The U.S. Geological Survey shall not be held liable for improper or incorrect use of the data described and (or) contained herein. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof.
  4. How can I download or order the data?
    • Availability in digital form:
      Data format: This dataset provides movable bed, sea floor interaction, experiment video data with a graphical representation of flow velocity. Images were collected during small-oscillatory flow tunnel laboratory experiments at the Naval Research Laboratory, Stennis Space Center, Stennis Mississippi and includes the associated metadata. in format MP4 (version 1) Mpeg-4 video file Size: 169.6
      Network links: https://coastal.er.usgs.gov/data-release/doi-F76D5R69/data/2017_309_DD_SFI_preview.zip
    • Cost to order the data: none

  5. What hardware or software do I need in order to use the data set?
    This zip file contains data available in mpeg-4 (MP4) video file format. The user must have software capable of reading .mp4 video file format to use these data.

Who wrote the metadata?

Dates:
Last modified: 16-Nov-2023
Metadata author:
Robert L. Jenkins III
U.S. Geological Survey
Researcher III
600 Fourth Street South
Saint Petersburg, Florida
USA

727-502-8138 (voice)
727-502-8182 (FAX)
rljenkins@usgs.gov
Metadata standard:
Content Standards for Digital Geospatial Metadata (FGDC-STD-001-1998)

This page is <https://cmgds.marine.usgs.gov/catalog/spcmsc/aSOA_SFI_preview_metadata.faq.html>
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