http://lod.bco-dmo.org/id/dataset/1003429
eng; USA
utf8
dataset
Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
2026-08-04
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Particle characteristics of low and high optical-density particles (LODP and HODP) from Focused Shadowgraph Imaging (FoSI) in the NE Atlantic, Jan-Mar 2023 (DESAFÍO)
2026-08-04
publication
2026-08-04
revision
Woods Hole Oceanographic Institution (WHOI BCO-DMO)
2026-08-08
publication
https://doi.org/10.26008/1912/bco-dmo.1003429.1
Alexander Boris Bochdansky
Old Dominion University
principalInvestigator
Santiago Hernández-León
Universidad de Las Palmas de Gran Canaria
principalInvestigator
Maria Couret
Universidad de Las Palmas de Gran Canaria
principalInvestigator
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
publisher
Cite this dataset as: Huang, H., Bochdansky, A. B., Couret, M., Hernández-León, S. (2026) Particle characteristics of low and high optical-density particles (LODP and HODP) from Focused Shadowgraph Imaging (FoSI) in the NE Atlantic, Jan-Mar 2023 (DESAFÍO). Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2026-08-04 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.1003429.1 [access date]
Dataset Description: <p>Note on spatial and temporal resolution: The overall date and location range (lat,lon bounding box) were added to the dataset metadata.&nbsp; More detailed spatial and temporal resolution per profile is included in the related dataset:</p>
<p>Vertical profiles of Low and high-optical-density particles (LODP and HODP) and CTD hydrographic data from Focused Shadowgraph Imaging (FoSI) in the NE Atlantic, Jan–Mar 2023 (DESAFÍO)<br />
https://www.bco-dmo.org/dataset/1003447<br />
<br />
Acronyms:&nbsp;<br />
<br />
DESAFÍO = DisEntangling Seasonality of Active Flux in the Ocean (expedition name)<br />
FoSI = Focused Shadowgraph Imaging<br />
LODP = Low Optical-Density Particles<br />
HODP = High Optical-Density Particles<br />
OD = Optical Density<br />
ESD =&nbsp;equivalent spherical diameter<br />
AZ = Azores<br />
CI = Canary Islands<br />
OO = Open Ocean<br />
RGF = Relative Gel Fraction<br />
ART ANOVA = Aligned Rank Transform (ART)&nbsp;Analysis of Variance (ANOVA)<br />
ANCOVA = Analysis of Covariance</p> Methods and Sampling: <p>Particle data were collected during the DESAFÍO expedition (DisEntangling Seasonality of Active Flux in the Ocean; PID2020-118118RB-100) in the Northeastern subtropical Atlantic Ocean, from 31 January to 2 March 2023. Sampling spanned a transect between the Azores (AZ; 41°5'32.39"N, 24°58'41.00"W) and the Canary Islands (CI; 28°41'00.00"N, 13°12'2.40"W). Twenty-two CTD/rosette casts were grouped into three geographic regions — CI (casts 1–6), the open-ocean station OO (casts 7–14, west of CI and south of the Azores), and AZ (casts 15–22) — and particle and hydrographic data within each cast were further partitioned into three depth strata: epipelagic (≤200 m), mesopelagic (200–1,000 m), and bathypelagic (&gt;1,000 m). Four casts (5, 6, 18, and 20) have incomplete particle-image profiles due to unexpected camera shutdowns, likely caused by low battery voltage.</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-2128438 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=2128438
completed
Alexander Boris Bochdansky
Old Dominion University
757-683-4933
Ocean, Earth and Atmospheric Sciences 4600 Elkhorn Ave.
Norfolk
VA
23529
USA
ABochdan@odu.edu
pointOfContact
Santiago Hernández-León
Universidad de Las Palmas de Gran Canaria
shernandezleon@ulpgc.es
pointOfContact
Maria Couret
Universidad de Las Palmas de Gran Canaria
maria.couret101@alu.ulpgc.es
pointOfContact
asNeeded
Dataset Version: 1
Unknown
particlePool
depth_zone
regions
ESD
aspect_ratio
OD
circularity
Focused Shadowgraph Imaging (FoSI) System
Sea-Bird SBE911 Plus CTD
theme
None, User defined
sample description
site description
site
ESD (Equivalent spherical diameter)
optical_density
featureType
BCO-DMO Standard Parameters
Camera
CTD Sea-Bird SBE 911plus
instrument
BCO-DMO Standard Instruments
PID2020-118118RB-100
service
Deployment Activity
Northeast Atlantic
place
Locations
otherRestrictions
otherRestrictions
Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use.
Linking optical characteristics of small particles (50 - 500 micrometer) with their sinking velocities in the mesopelagic environment
https://osprey.bco-dmo.org/project/882082
Linking optical characteristics of small particles (50 - 500 micrometer) with their sinking velocities in the mesopelagic environment
<p>NSF Award Abstract</p>
<p>Globally, the ocean removes more carbon dioxide than it releases into the atmosphere storing a portion of the excess carbon in the deep sea. Sinking particles, both living plankton and non-living detritus, are major contributors to this flux of carbon. Modern camera systems and image analysis techniques have made it possible to count, measure and classify these particles, thus providing oceanographers with a tool to estimate carbon transfers to the deep ocean at high resolution in space and time. Unfortunately, it is not enough to know the sizes of particles to estimate how fast these particles sink because shape and particle density also influence the sinking velocity. This project examines the velocities of individual particles as they sink into the deep ocean using a camera attached to a particle trap. For each of these particles, classification criteria, such as size, shape factors, optical density, and in the case of plankton, taxonomic identification, is determined and compared to their individual sinking velocities. This information serves to calculate overall sinking velocities from surveys of particles in the water column and thereby produce more reliable estimates of carbon fluxes from camera images. This project supports technology development in underwater imaging systems, graduate and undergraduate student education, and science literacy initiatives for middle-school students and their mentors through public outreach programs.</p>
<p>Shipboard and autonomous vehicle surveys of oceanic particle inventories hold great promise for estimating carbon fluxes at high temporal and spatial resolutions. However, while the sinking velocities of larger particles such as foraminifera shells and fecal pellets of salps, krill, and larger copepods are relatively well constrained, the dynamics of the smaller particle size pool (50–500 micrometers) remain more elusive. Despite their size and presumed slow sinking velocities, small particles occur in large numbers in the mesopelagic layer and sediment-trap material. Their abundance in the mesopelagic could be the result of deep mixing, or small particles could be remnants of digested larger particles, particles with a high excess density such as lithogenic dust particles, minipellets egested by protists, protist spores, or the result of fragmentation at depth due to the activity of flux feeders, among other possibilities. This project addresses some unanswered questions about the small particle pool by linking individually-resolved optical features with sinking velocities. Using Stokes’ law, excess density is being estimated from size and sinking velocity and then assigned to particles from optical surveys. A horizontally installed camera system records sinking velocities, sizes, and features of particles in a sediment trap attached to the Oceanic Flux Program mooring array. The recorded particles are being characterized using 1) classic image analysis, taking various shape factors into account; 2) opacity of individual particles; and 3) image classification with supervised and unsupervised deep learning using convolutional neural networks. A second identical camera surveys the particle inventory at the same station and time in the water column to integrate flux estimates over the existing and undisturbed particle pool. Niskin bottle samples and microscopic examination of particles augment the interpretation of image data. The results of this project contribute to the overarching goal of achieving higher predictive power for carbon flux models based on optical particle surveys.</p>
<p>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.</p>
Mesopelagic particles
largerWorkCitation
project
eng; USA
oceans
Northeast Atlantic
-25.147
-13.2007
28.7
41.09233
2023-01-31
2023-03-02
North Atlantic
0
BCO-DMO catalogue of parameters from Particle characteristics of low and high optical-density particles (LODP and HODP) from Focused Shadowgraph Imaging (FoSI) in the NE Atlantic, Jan-Mar 2023 (DESAFÍO)
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
http://lod.bco-dmo.org/id/dataset-parameter/1004065.rdf
Name: particlePool
Units: unitless
Description: <p>LODP (low optical-density particles, recognized at threshold > 11) or HODP (high optical-density particles, recognized at threshold > 29)</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004066.rdf
Name: depth_zone
Units: unitless
Description: <p>epi: epipelagic zone (0-200m);meso: mesopelagic zone (200-1000m); bathy: bathypelagic zone (>1000m)</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004067.rdf
Name: regions
Units: unitless
Description: <p>The Canary Islands region (CI; casts 1–6), the oligotrophic ocean region (OO; casts 7–14), and the Azores region (AZ; casts 15–22)</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004068.rdf
Name: ESD
Units: micrometers
Description: <p>Equivalent spherical diameter</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004069.rdf
Name: aspect_ratio
Units: unitless
Description: <p>The ratio of MajorAxisLength and MinorAxisLength</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004070.rdf
Name: OD
Units: unitless
Description: <p>Optical density calibrated from intensity (ranging from 0.04-1)</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004071.rdf
Name: circularity
Units: unitless
Description: <p>A measure of how circular a particle is, calculated from 4*pi*Area/Perimeter^2</p>
GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
https://doi.org/10.26008/1912/bco-dmo.1003429.1
download
onLine
dataset
<p>Particle data were collected during the DESAFÍO expedition (DisEntangling Seasonality of Active Flux in the Ocean; PID2020-118118RB-100) in the Northeastern subtropical Atlantic Ocean, from 31 January to 2 March 2023. Sampling spanned a transect between the Azores (AZ; 41°5'32.39"N, 24°58'41.00"W) and the Canary Islands (CI; 28°41'00.00"N, 13°12'2.40"W). Twenty-two CTD/rosette casts were grouped into three geographic regions — CI (casts 1–6), the open-ocean station OO (casts 7–14, west of CI and south of the Azores), and AZ (casts 15–22) — and particle and hydrographic data within each cast were further partitioned into three depth strata: epipelagic (≤200 m), mesopelagic (200–1,000 m), and bathypelagic (&gt;1,000 m). Four casts (5, 6, 18, and 20) have incomplete particle-image profiles due to unexpected camera shutdowns, likely caused by low battery voltage.</p>
Specified by the Principal Investigator(s)
<p>Particle images were processed following the pipeline of Huang and Bochdansky (2025), with analysis restricted to particles ≥23.5 μm (linear dimension) to exclude single-pixel noise. Two particle pools were defined by thresholds calibrated with optical density (OD): low-OD particles (LODP; threshold 11, OD = 0.1466), which include the numerically dominant gel particles, and high-OD particles (HODP; threshold 29, OD = 0.2246), representing more opaque particles comparable to those detected by other optical instruments. Morphological metrics (equivalent spherical diameter (ESD), optical density, aspect ratio and circularity) were extracted using MATLAB function regionprops(), with OD calibrated from brightness via an ensemble model. Both particle pools were resolved to 1-m depth bins for downstream analysis, including Theil–Sen regression with Mann–Kendall trend testing, Aligned Rank Transform (ART) ANOVA to assess regional and depth effects on abundance and total particle volume, Kolmogorov–Smirnov and Wilcoxon rank-sum tests for distributional/median comparisons, Wilcoxon signed-rank tests for paired day–night comparisons, calculation of the Relative Gel Fraction (RGF) from LODP and HODP abundances, and particle number spectrum analysis with ANCOVA to test slope homogeneity across regions and depths.</p>
<p>&nbsp;</p>
<p><em>Huang, H., &amp; Bochdansky, A. B. (2025). Optimizing an image analysis protocol for ocean particles in focused shadowgraph imaging systems. Frontiers in Marine Science, 12, 1539828.</em></p>
Specified by the Principal Investigator(s)
- Loaded particle_characteristics_combined_with_regions.csv from submission storage into table 1003429_v1_fosi-particle-characteristics, using comma delimiter, first row as header, empty string and "nd" set as missing values, casting all columns to strings on load
- Set data types for columns: ESD (number), OD (number), aspect_ratio (number), circularity (number), depth_zone (string), particlePool (string), regions (string)
- Updated column metadata with descriptions, standard name IDs, and supplied units
- Dumped final table to output as 1003429_v1_fosi-particle-characteristics.csv, with unique lat/lon extraction enabled
Specified by BCO-DMO Data Managers
asNeeded
7.x-1.1
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
Focused Shadowgraph Imaging (FoSI) System
Focused Shadowgraph Imaging (FoSI) System
PI Supplied Instrument Name: Focused Shadowgraph Imaging (FoSI) System PI Supplied Instrument Description:Vertical profiles of conductivity, temperature, dissolved oxygen, fluorescence, and turbidity were measured from the surface to 4,000 m using a Sea-Bird SBE911 Plus CTD fitted with a Sea-Bird SBE43 dissolved-oxygen sensor and a Wet Labs ECO-NTU-RTD fluorometer/turbidimeter, all mounted on the rosette sampler; these profiles were binned to 1 dbar. Particle imagery was collected concurrently using a Focused Shadowgraph Imaging (FoSI) System attached to the base of the CTD rosette, providing particle data co-located in space and time with the CTD sensor suite. The configuration of FoSI was described by Bochdansky et al. (2022) and Huang and Bochdansky (2025). The FoSI imaged particles at a resolution of 11.75 μm/pixel. Instrument Name: Camera Instrument Short Name:camera Instrument Description: All types of photographic equipment including stills, video, film and digital systems. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/311/
Sea-Bird SBE911 Plus CTD
Sea-Bird SBE911 Plus CTD
PI Supplied Instrument Name: Sea-Bird SBE911 Plus CTD PI Supplied Instrument Description:Vertical profiles of conductivity, temperature, dissolved oxygen, fluorescence, and turbidity were measured from the surface to 4,000 m using a Sea-Bird SBE911 Plus CTD fitted with a Sea-Bird SBE43 dissolved-oxygen sensor and a Wet Labs ECO-NTU-RTD fluorometer/turbidimeter, all mounted on the rosette sampler; these profiles were binned to 1 dbar. Particle imagery was collected concurrently using a Focused Shadow Imaging System (FoSI) attached to the base of the CTD rosette, providing particle data co-located in space and time with the CTD sensor suite. The configuration of FoSI was described by Bochdansky et al. (2022) and Huang and Bochdansky (2025). The FoSI imaged particles at a resolution of 11.75 μm/pixel. Instrument Name: CTD Sea-Bird SBE 911plus Instrument Short Name:CTD SBE 911plus Instrument Description: The Sea-Bird SBE 911 plus is a type of CTD instrument package for continuous measurement of conductivity, temperature and pressure. The SBE 911 plus includes the SBE 9plus Underwater Unit and the SBE 11plus Deck Unit (for real-time readout using conductive wire) for deployment from a vessel. The combination of the SBE 9 plus and SBE 11 plus is called a SBE 911 plus. The SBE 9 plus uses Sea-Bird's standard modular temperature and conductivity sensors (SBE 3 plus and SBE 4). The SBE 9 plus CTD can be configured with up to eight auxiliary sensors to measure other parameters including dissolved oxygen, pH, turbidity, fluorescence, light (PAR), light transmission, etc.). more information from Sea-Bird Electronics Community Standard Description: http://vocab.nerc.ac.uk/collection/L22/current/TOOL0058/
Cruise: PID2020-118118RB-100
PID2020-118118RB-100
R/V Sarmiento de Gamboa
vessel
PID2020-118118RB-100
Santiago Hernández-León
Universidad de Las Palmas de Gran Canaria
R/V Sarmiento de Gamboa
vessel