Laboratory Observations of Artificial Sand and Oil Agglomerates Video and Velocity Data: False-Floor Experiment Interpretive Video

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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: False-Floor Experiment Interpretive Video
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:
This dataset (2017_309_DD_FF_video.zip) contains interpretive video of false-floor experiment incipient motion video data with graphical representations of flow velocity and shear stress 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: False-Floor Experiment Interpretive Video: 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., 2017, 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: -89.651
    East_Bounding_Coordinate: -89.557
    North_Bounding_Coordinate: 30.395
    South_Bounding_Coordinate: 30.345
  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_FF_video
    Interpretive video product of false-floor experiment incipient motion video data, which includes a graphical representation of flow velocity and shear stress. (Source: U.S. Geological Survey)
    aSOA ID
    Unique, 3-character alpha-numeric string created to denote size class, shape, and number of artificial sand and oil agglomerate. (Source: U.S. Geological Survey) String used to identify the artificial sand and oil agglomerate featured in the interpretive video product. The first character (a number) refers to the aSOA’s size class, the second character (a letter) refers to the shape, and the third character (a number) refers to the unique aSOA of a given size class and shape (see Dalyander et al. (2015)).
    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) for the period surrounding incipient motion is included in each .mp4 file; the video is positioned above a graphical representation of the water velocity and shear stress.
    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.
    Tau (Pa)
    Shear stress calculated using methods presented in Soulsby, 1997 and water velocity. (Source: U.S. Geological Survey) Record of shear stress (tau, t), which coincides with water velocity and video record time period.
    Instant of Incipient Motion
    Experiment time at which aSOA experiences incipient motion. (Source: U.S. Geological Survey) Single time point of incipient motion in video and velocity time record (represented on the graph by a dashed line).
    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 video 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 experiment conducted at the Naval Research Laboratory (NRL), Stennis Space Center, Mississippi. The information contained within the videos is needed to capture artificial sand and oil agglomerate incipient motion, and flow velocity at time of incipient motion, under ideal conditions, to test shear stress based incipient motion parameterizations. The information contained within the videos is also needed to capture exhumation and burial processes of artificial sand and oil agglomerates. This dataset contains video of aSOAs in a small-oscillatory flow tunnel from the false-floor experiment, as well as times of incipient motion, aSOA identifiers, graphical representations of observed flow velocity, and graphical representations of calculated shear stress based on observed flow velocity. Observed flow velocities, which provide additional information about aSOA incipient motion, were also collected during this experiment (see 2017_309_DD_FF_velocity_stress.zip) and are 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: 10-Mar-2014 (process 1 of 17)
    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: 10-Mar-2014 (process 2 of 17)
    The onset of incipient motion was precisely measured with a Bed LAser Surface Tracking (BLAST) System. Two 520 nm, 75-degree fan beam, continuous-wave lasers were mounted above the tank and projected a 3-mm wide and 1-m long laser line along the tank floor, parallel to the flow direction. The aSOAs were placed to intersect the laser lines so that the two Canon 7D DSLR cameras captured 1080p HD video at 30 frames per second of the laser line projected on to the aSOAs and the bed floor. 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: 10-Mar-2014 (process 3 of 17)
    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: 10-Mar-2014 (process 4 of 17)
    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: 10-Mar-2014 (process 5 of 17)
    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 17)
    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 17)
    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: 21-Aug-2015 (process 8 of 17)
    JPEG images extracted from raw video data were then processed in MATLAB using a script called 'LaserMovieMain_rjv4.m' (NRL & SPCMSC script), which located the laser line in each image based on the local maxima in image color contrast. The laser line location was extracted in pixel coordinates. A time series of laser line location, in pixel coordinates, was formed for the entire experiment segment. Finallly the time series of laser line location, in pixel coordinates, was converted into real world coordinates (measured in meters) based on a calibration image taken prior to the experiment. 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: 15-Sep-2015 (process 9 of 17)
    For large aSOA, laser line location time series revealed the instance of aSOA incipient motion as indicated by change in the laser line location. Once the instance was found the frame number was recorded, manually, and the time of incipient motion in seconds relative to the beginning of the video was calculated as the frame number divided by video framerate, in 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 10 of 17)
    In most instances, incipient motion was not discernible by laser line location. In these cases, the frame and time at which incipient motion took place was found, by visual frame-by-frame inspection of extracted JPEGS of the raw video data. Once the instance was found the frame number was recorded manually and the time of incipient motion in seconds (relative to the beginning of the video) was calculated as frame number divided by video framerate, in 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 11 of 17)
    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. 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 12 of 17)
    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). The interpretive video products are limited to 42 seconds in length; only velocity data 30 seconds prior to and 12 seconds proceeding incipient motion were 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: 24-Sep-2015 (process 13 of 17)
    Shear stress input was generated by calculating shear stress based on shear stress parameterization presented in Soulsby, 1997, using aSOA diameter, flow velocity at time of incipient motion, and an empirical value for orbital excursion amplitude. The empirical value for orbital excursion amplitude was calculated for each experiment record from the de-spiked along-tank velocity. The negative-to-positive zero crossings were identified and the times of these upward zero-crossings were recorded. A matrix of upward zero-crossings was created to identify individual waves. Given flow velocity and time between upward zero-crossings, displacements were calculated. Orbital excursion amplitude is defined as one quarter of this displacement. The orbital excursion amplitude used in the stress calculation is the median value for a given record, excluding the first and last sixty seconds to avoid errors introduced by experiment ramp up and ramp down. 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 14 of 17)
    Video data input for the video data product was selected from a 42-second window surrounding incipient motion. The interpretive video products are limited to 42 seconds in length; video data 30 seconds prior to and 12 seconds proceeding incipient motion were selected. 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 15 of 17)
    Interpretive video products were 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, shear stress, indicator of the moment of incipient motion, 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, shear stress, the indicator of the moment of incipient motion, 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.'
    
    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 16 of 17)
    The file size of the .avi file created in the preevious step was reduced via free compression software 'Avidemux', prior to saving the final file in '.mp4' format. 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 17 of 17)
    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?
    Soulsby, R. L., 1997, Dynamics of marine sands: A manual for practical applications: Thomas Telford Publications, London, England.

    Online Links:

    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; however, velocity data is unavailable for False_Floor_4E2.mp4 and False_Floor_4R2.mp4. 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. Videos are shot in a darkened room, with the exception of "False_Floor_1E5.mp4" which was shot with the lights on. This was unintentional but did not effect the results presented in this data release.

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_FF_video.zip, contains the following MP4 video files: False_Floor_1E1.mp4, False_Floor_1E4.mp4, False_Floor_1E5.mp4, False_Floor_1R3.mp4, False_Floor_1R5.mp4, False_Floor_2E1.mp4, False_Floor_2E5.mp4, False_Floor_2R1.mp4, False_Floor_3E2.mp4, False_Floor_3R3.mp4, False_Floor_4E2.mp4, False_Floor_4R2.mp4, False_Floor_5E1.mp4, False_Floor_5R2.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 false-floor experiment incipient motion video data with a graphical representation of flow velocity and shear stress. 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: 142.7
      Network links: https://coastal.er.usgs.gov/data-release/doi-F76D5R69/data/2017_309_DD_FF_video.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: 13-Oct-2020
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_FF_video_metadata.faq.html>
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