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opencc-by-4.0Apr 2018View details →

Underwater hyperspectral scan from India, scene 12

Underwater hyperspectral scan from India, scene 12 Used previously in publication Zimmermann, Nevala, Yoshimatsu et al., 2018, Current Biology, in press.

opencc-by-4.0Apr 2018View details →

Underwater hyperspectral scan from India, scene 1

Underwater hyperspectral scan from India, scene 1 Used previously in publication Zimmermann, Nevala, Yoshimatsu et al., 2018, Current Biology, in press.

opencc-by-4.0Apr 2018View details →

Underwater hyperspectral scan from India, scene 30

Underwater hyperspectral scan from India, scene 30 Used previously in publication Zimmermann, Nevala, Yoshimatsu et al., 2018, Current Biology, in press.

Underwater images collected by Scuba diving in St-Gilles, Réunion - 2015-06-11

This dataset was collected by Scuba diving in St-Gilles, Réunion - 2015-06-11. Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation. These images can be annotated and shared to train IA models which can in turn predict the objects on the images. We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps. Underwater Images Collected by Scuba Diving in Réunion Island during the Hyscores Project. For more details, visit the <a href="https://archimer.ifremer.fr/doc/00350/46122/" target="_blank">Hyscores Project</a>. <h2> Generic folder structure </h2> YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number ├── DCIM : folder to store videos and photos depending on the media collected. ├── GPS : folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. │ ├── BASE : files coming from rtk station or any static positioning instrument. │ └── DEVICE : files coming from the device. ├── METADATA : folder with general information files about the session. ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. │ ├── BATHY : output folder for bathymetry raw data extracted from mission logs. │ ├── FRAMES : output folder for georeferenced frames extracted from DCIM videos. │ ├── IA : destination folder for image recognition predictions. │ └── PHOTOGRAMMETRY : destination folder for reconstructed models in photogrammetry. └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot, mission plan etc.). <h2> Software </h2> All the raw data was processed using our <a href="https://github.com/SeatizenDOI/plancha-workflow/releases/tag/v1.0.3" target="_blank">worflow</a>. All predictions were generated by our <a href="https://github.com/SeatizenDOI/plancha-inference/releases/tag/v1.0.0" target="_blank">inference pipeline</a>. You can find all the necessary scripts to download this data in this <a href="https://github.com/SeatizenDOI/zenodo-tools" target="_blank">repository</a>. Enjoy your data with <a href="https://github.com/SeatizenDOI" target="_blank">SeatizenDOI</a>!

Underwater images collected by Scuba diving in La-Saline, Réunion - 2015-06-16

This dataset was collected by Scuba diving in La-Saline, Réunion - 2015-06-16. Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation. These images can be annotated and shared to train IA models which can in turn predict the objects on the images. We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps. Underwater Images Collected by Scuba Diving in Réunion Island during the Hyscores Project. For more details, visit the <a href="https://archimer.ifremer.fr/doc/00350/46122/" target="_blank">Hyscores Project</a>. <h2> Generic folder structure </h2> YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number ├── DCIM : folder to store videos and photos depending on the media collected. ├── GPS : folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. │ ├── BASE : files coming from rtk station or any static positioning instrument. │ └── DEVICE : files coming from the device. ├── METADATA : folder with general information files about the session. ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. │ ├── BATHY : output folder for bathymetry raw data extracted from mission logs. │ ├── FRAMES : output folder for georeferenced frames extracted from DCIM videos. │ ├── IA : destination folder for image recognition predictions. │ └── PHOTOGRAMMETRY : destination folder for reconstructed models in photogrammetry. └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot, mission plan etc.). <h2> Software </h2> All the raw data was processed using our <a href="https://github.com/SeatizenDOI/plancha-workflow/releases/tag/v1.0.3" target="_blank">worflow</a>. All predictions were generated by our <a href="https://github.com/SeatizenDOI/plancha-inference/releases/tag/v1.0.0" target="_blank">inference pipeline</a>. You can find all the necessary scripts to download this data in this <a href="https://github.com/SeatizenDOI/zenodo-tools" target="_blank">repository</a>. Enjoy your data with <a href="https://github.com/SeatizenDOI" target="_blank">SeatizenDOI</a>!

Underwater images collected by Scuba diving in St-Gilles, Réunion - 2015-12-10

This dataset was collected by Scuba diving in St-Gilles, Réunion - 2015-12-10. Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation. These images can be annotated and shared to train IA models which can in turn predict the objects on the images. We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps. Underwater Images Collected by Scuba Diving in Réunion Island during the Hyscores Project. For more details, visit the <a href="https://archimer.ifremer.fr/doc/00350/46122/" target="_blank">Hyscores Project</a>. <h2> Generic folder structure </h2> YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number ├── DCIM : folder to store videos and photos depending on the media collected. ├── GPS : folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. │ ├── BASE : files coming from rtk station or any static positioning instrument. │ └── DEVICE : files coming from the device. ├── METADATA : folder with general information files about the session. ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. │ ├── BATHY : output folder for bathymetry raw data extracted from mission logs. │ ├── FRAMES : output folder for georeferenced frames extracted from DCIM videos. │ ├── IA : destination folder for image recognition predictions. │ └── PHOTOGRAMMETRY : destination folder for reconstructed models in photogrammetry. └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot, mission plan etc.). <h2> Software </h2> All the raw data was processed using our <a href="https://github.com/SeatizenDOI/plancha-workflow/releases/tag/v1.0.3" target="_blank">worflow</a>. All predictions were generated by our <a href="https://github.com/SeatizenDOI/plancha-inference/releases/tag/v1.0.0" target="_blank">inference pipeline</a>. You can find all the necessary scripts to download this data in this <a href="https://github.com/SeatizenDOI/zenodo-tools" target="_blank">repository</a>. Enjoy your data with <a href="https://github.com/SeatizenDOI" target="_blank">SeatizenDOI</a>!

Figure 11 in First researches of the underwater ecosystem communities of an underground channel built in 1950s (Balaklava bay, Sevastopol)

Figure 11. Variabilities of high meiobenthic taxa by their abundance (103 ind./m2) (colored bars) and by their total number (dotted line): A – in the bottom sediments, B – in the biofouling of the channel walls at the depth of 1.5 meters.

Figure 8 in First researches of the underwater ecosystem communities of an underground channel built in 1950s (Balaklava bay, Sevastopol)

Figure 8. Quantitative representation of macrozoobenthos in the channel wall biofouling at a depth of 1.5 m: A – by abundance (103 ind./m2), B – by biomass (g/m2).

Figure 6 in First researches of the underwater ecosystem communities of an underground channel built in 1950s (Balaklava bay, Sevastopol)

Figure 6. Channel wall biofoulings at the point 4: A, B – underwater edge on the northeast wall; C – at the depth of 1.5 m on the northeast wall; D, E – underwater edge on the southeast wall; F – at the depth of 1.5 m on the southeast wall.

Figure 5. A in First researches of the underwater ecosystem communities of an underground channel built in 1950s (Balaklava bay, Sevastopol)

Figure 5. A – General view of the biofouling at the point 3, B – Porifera colonies, C – Mussels druze on the halyard.

Figure 2 in First researches of the underwater ecosystem communities of an underground channel built in 1950s (Balaklava bay, Sevastopol)

Figure 2. Topography of anthropogenic objects in the underground channel on the base of submarines in Balaklava and benthic sampling stations. Topography of anthropogenic objects in the underground channel at the submarine base in Balaklava and the benthos sampling station.

Figure 1 in First researches of the underwater ecosystem communities of an underground channel built in 1950s (Balaklava bay, Sevastopol)

Figure 1. Museum of Military History of Fortifications "Balaklava" in Mount Tavros: A – entrance to the Museum from the side of the Balaklava Bay embankment (photo by A. Zatsepin); B – northern entrance part of the channel from the side of the embankment of the bay; C – southern entrance part of the channel; D, E – internal view of the channel with artificial illumination in its different parts.

Figure 9 in First researches of the underwater ecosystem communities of an underground channel built in 1950s (Balaklava bay, Sevastopol)

Figure 9. The species number ratio of higher taxa in the channel walls macrobiofouling, in comparison with similar data on rocks other areas of the Crimean coast.

opencc-by-4.0Oct 2018View details →

Fig. 1 in Physiological responses of anti-predation in prey fish to the threat of piscivorous fish in different underwater visibility conditions

Fig. 1. Mean and standard error of plasma cortisol levels for Astyanax bimaculatus (Linnaeus, 1758) shoals in treatments with clear (white box) and turbid water (striped box). Different letters above bars indicate significant differences at P<0.05 in the Kruskal Wallis test between predator types. There were no differences between plasma cortisol levels in clear and turbid water treatments.

Underwater hyperspectral data of Vigo survey fieldwork Sept. 2023 (Reflectance Converted)

<h2>Abstract</h2> Reflectance converted data of UHI data from Vigo fieldwork Sept 2023 survey. Data were recorded at three different sea zones in Vigo. This depository contains data generated within the European S34 project. <h2>Metadata Information</h2> <table> <tbody> <tr> <td> Identification </td> </tr> <tr> <td> Full Title </td> <td> Underwater hyperspectral data of Vigo survey fieldwork Sept 2023 </td> </tr> <tr> <td> Abstract </td> <td> Reflectance converted data of UHI data from Vigo fieldwork Sept 2023 survey. Data were recorded at three different sea zones in Vigo. </td> </tr> <tr> <td> Keywords </td> <td> Reflectance estimated underwater hyperspectral, UHI, seabed, mineral, sea region </td> </tr> <tr> <td> Pilot area </td> <td> Ria de Vigo </td> </tr> <tr> <td> Associated resources </td> <td> Report </td> </tr> <tr> <td> Language </td> <td> English </td> </tr> <tr> <td> URL </td> <td> / </td> </tr> <tr> <td> Categories </td> <td> Bio-geographical regions </td> </tr> <tr> <td> Temporal reference </td> </tr> <tr> <td> Creation date (dd.mm.yyyy) </td> <td> 30.11.2023 </td> </tr> <tr> <td> Revision date (dd.mm.yyyy) </td> <td> 30.11.2023 </td> </tr> <tr> <td> Quality and validity </td> </tr> <tr> <td> Representation type </td> <td> Other </td> </tr> <tr> <td> Format </td> <td> HDF5 </td> </tr> <tr> <td> Lineage </td> <td> / </td> </tr> <tr> <td> Spatial resolution </td> <td> 1.5m </td> </tr> <tr> <td> Positional accuracy </td> <td> / </td> </tr> <tr> <td> Maintenance information </td> <td> / </td> </tr> <tr> <td> Coordinate system </td> <td> EPSG 3035 </td> </tr> <tr> <td> Constranits related to access and use </td> </tr> <tr> <td> Use limitation </td> <td> / </td> </tr> <tr> <td> Access constraint </td> <td> / </td> </tr> <tr> <td> Public/Private </td> <td> Public </td> </tr> <tr> <td> Responsible organisation </td> </tr> <tr> <td> Responsible Contact </td> <td> Ecotone AS, info@ecotone.com </td> </tr> <tr> <td> Responsible Party </td> <td> Ecotone AS </td> </tr> <tr> <td> Metadata on metadata </td> </tr> <tr> <td> Contact </td> <td> Ecotone AS, info@ecotone.com </td> </tr> <tr> <td> Metadata language </td> <td> English </td> </tr> </tbody> </table>

Underwater hyperspectral data of Vigo survey fieldwork Sept. 2023 (Radiance Converted)

<h2>Abstract</h2> Radiance converted data of UHI data from Vigo fieldwork Sept 2023 survey. Data were recorded at three different sea zones in Vigo. This depositry contains data generated within the European S34 project. <h2>Metadata Information</h2> <table> <tbody> <tr> <td> Identification </td> </tr> <tr> <td> Full Title </td> <td> Underwater hyperspectral data of Vigo survey fieldwork Sept 2023 </td> </tr> <tr> <td> Abstract </td> <td> Radiance converted data of UHI data from Vigo fieldwork Sept 2023 survey. Data were recorded at three different sea zones in Vigo. </td> </tr> <tr> <td> Keywords </td> <td> Radiance converted underwater hyperspectral image data, UHI, seabed, mineral, sea region </td> </tr> <tr> <td> Pilot area </td> <td> Ria de Vigo </td> </tr> <tr> <td> Associated resources </td> <td> Report </td> </tr> <tr> <td> Language </td> <td> English </td> </tr> <tr> <td> URL </td> <td> / </td> </tr> <tr> <td> Categories </td> <td> Bio-geographical regions </td> </tr> <tr> <td> Temporal reference </td> </tr> <tr> <td> Creation date (dd.mm.yyyy) </td> <td> 30.11.2023 </td> </tr> <tr> <td> Revision date (dd.mm.yyyy) </td> <td> 30.11.2023 </td> </tr> <tr> <td> Quality and validity </td> </tr> <tr> <td> Representation type </td> <td> Other </td> </tr> <tr> <td> Format </td> <td> HDF5 </td> </tr> <tr> <td> Lineage </td> <td> / </td> </tr> <tr> <td> Spatial resolution </td> <td> 1.5m </td> </tr> <tr> <td> Positional accuracy </td> <td> / </td> </tr> <tr> <td> Maintenance information </td> <td> / </td> </tr> <tr> <td> Coordinate system </td> <td> EPSG 3035 </td> </tr> <tr> <td> Constranits related to access and use </td> </tr> <tr> <td> Use limitation </td> <td> / </td> </tr> <tr> <td> Access constraint </td> <td> / </td> </tr> <tr> <td> Public/Private </td> <td> Public </td> </tr> <tr> <td> Responsible organisation </td> </tr> <tr> <td> Responsible Contact </td> <td> Ecotone AS, info@ecotone.com </td> </tr> <tr> <td> Responsible Party </td> <td> Ecotone AS </td> </tr> <tr> <td> Metadata on metadata </td> </tr> <tr> <td> Contact </td> <td> Ecotone AS, info@ecotone.com </td> </tr> <tr> <td> Metadata language </td> <td> English </td> </tr> </tbody> </table>

FIGURE 12 in The Cuban Crocodile (Crocodylus rhombifer) from Late Quaternary Underwater Cave Deposits in the Dominican Republic

FIGURE 12. Map of the West Indies showing the location of Late Quaternary sites containing crocodiles. Fossil samples from Abaco and Grand Bahama in the Bahamas, Cuba, Dominican Republic, and Grand Cayman include skulls or partial skulls that can be confidently identified as the Cuban crocodile (Crocodylus rhombifer). All other records consist of fragmentary or isolated specimens identified as either Crocodylus sp. or Crocodylia indeterminate. Site numbers are as follows (sites 1–22 are from various islands in the Bahamas): Abaco (see Morgan and Albury, 2013, for an enlarged map of Abaco showing the location of these fossil sites): 1. Sawmill Sink; 2. Dan's Cave; 3. Ralph's Cave; 4. Nancy's Cave; 5. Lost Reel Cave. 6. Gilpin Point. Grand Bahama: 7. Bell Channel; 8. Anaconda Pond; 9. Mermaid's Lair. Eleuthera: 10. White Lake Cave; 11. Kelly's Blue Hole (= Bung Hole); 12. Mermaid's Pool; 13. Preacher's Cave. New Providence: 14. Banana Hole. San Salvador: 15. Hanna's Bananas. Great Exuma: 16. Isaac Bay Cave. Rum Cay: 17. Bobby's Cave. Crooked Island: 18. Pittstown Landing; 19. 1702 Cave. Acklins: 20. Rupert's Pond; 21. Delectable Bay. Mayaguana: 22. The Fountain. Grand Cayman (see Morgan and Albury, 2013, for an enlarged map of Grand Cayman showing the location of these fossil sites): 23. Crocodile Canal; 24. Prospect; 25. Chisholm Cow Well; 26. Connally Cow Well; 27. Queen Elizabeth II Botanic Park; 28. Furtherland Farms Cow Well; 29. Crab Cave. Cuba: 30. Cueva Lamas; 31. Las Breas de San Felipe; 32. Ciego Montero; 33. Casimbas de las Llanadas; 34. Caves of Cueiba. Jamaica: 35. Wallingford Roadside Cave; 36. Dairy Cave; 37. Bellevue. Hispaniola (Dominican Republic): 38. Oleg's Bat Cave; 39. Ni-Rahu (= Cueva de Lynn). Puerto Rico: 40. Cueva Salida. Mona Island: 41. Cueva de los Losetas.

FIGURE 11 in The Cuban Crocodile (Crocodylus rhombifer) from Late Quaternary Underwater Cave Deposits in the Dominican Republic

FIGURE 11. Modern skull of an American crocodile (Crocodylus acutus) from Lago Enriquillo, Dominican Republic (MNHNRD1) in A. dorsal, B. ventral, C. left lateral, and D. posterior views.

FIGURE 10 in The Cuban Crocodile (Crocodylus rhombifer) from Late Quaternary Underwater Cave Deposits in the Dominican Republic

FIGURE 10. Ilia of the Cuban crocodile (Crocodylus rhombifer) of Late Quaternary age from Oleg's Bat Cave, Dominican Republic (MHD 575). A. External and B. internal views of the right ilium; C. external and D. internal views of the left ilium.

FIGURE 9 in The Cuban Crocodile (Crocodylus rhombifer) from Late Quaternary Underwater Cave Deposits in the Dominican Republic

FIGURE 9. Limb bones of the Cuban crocodile (Crocodylus rhombifer) of Late Quaternary age from Oleg's Bat Cave, Dominican Republic. All limb bones are from the left side and are from the same associated individual (MHD 576). A. Humerus, B. radius, C. ulna, D. femur, E. tibia, F. fibula. In each pair of photographs, the anterior view is on the left and posterior view on the right.