Underwater images collected by an Autonomous Underwater Vehicle in Hermitage, Réunion - 2021-12-01

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Main Authors: Cathy Treguier, Magali Duval, Sylvain Bonhommeau, Victor Illien
Format: Recurso digital
Language:English
Published: Zenodo 2026
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_version_ 1866901094325551104
author Cathy Treguier
Magali Duval
Sylvain Bonhommeau
Victor Illien
author_facet Cathy Treguier
Magali Duval
Sylvain Bonhommeau
Victor Illien
contents <i>This dataset was collected by an Autonomous Underwater Vehicle in Hermitage, Réunion - 2021-12-01.</i> <br> <br><br>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.<br><br> This dataset is part of larger collection referencing numerous underwater and aerial images <a href="https://doi.org/10.5281/zenodo.11125847" target="_blank">Seatizen Altas</a>. Methods, tools and scientific objectives are also described in a dedicated data paper.<br> <br> This dataset was collected by an Autonomous Underwater Vehicle, Réunion - 2021-12 (project RECIF 3D) <br> This dataset was processed with tools developped by different subsequent projects - 2025-12 (projects PLANCHA, ...) <br> 3D reconstruction and mapping of Reunion coral ecosystems from underwater images.<br> <h2>Survey information</h2> <ul> <li> <strong> Camera</strong>: Prosilica</li> <li> <strong> Number of images</strong>: 140 </li> <li> <strong> Total size</strong>: 1.94 Gb</li> <li> <strong> Flight start</strong>: 2021:12:01 04:47:50 </li> <li> <strong> Flight end</strong>: 2021:12:01 04:50:09</li> <li> <strong> Flight duration</strong>: 0h 2min 19sec</li> <li> <strong> Max depth</strong>: 8.72 m</li> </ul> <h2> Generic folder structure </h2> YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number <br> ├── DCIM : folder to store videos and photos depending on the media collected. <br> ├── 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. <br> │ ├── BASE : files coming from rtk station or any static positioning instrument. <br> │ └── DEVICE : files coming from the device. <br> ├── METADATA : folder with general information files about the session. <br> ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. <br> │ ├── BATHY : output folder for bathymetry raw data extracted from mission logs. <br> │ ├── FRAMES : output folder for georeferenced frames extracted from DCIM videos. <br> │ ├── IA : destination folder for image recognition predictions. <br> │ └── PHOTOGRAMMETRY : destination folder for reconstructed models in photogrammetry. <br> └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot, mission plan etc.). <br> <h2> Software </h2> All the raw data was processed using our <a href="github.com/SeatizenDOI/recif3D-workflow" target="_blank">worflow</a>. <br>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>. <br>Enjoy your data with <a href="https://github.com/SeatizenDOI" target="_blank">SeatizenDOI</a>! <br>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_18210001
institution Zenodo
language eng
publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle Underwater images collected by an Autonomous Underwater Vehicle in Hermitage, Réunion - 2021-12-01
Cathy Treguier
Magali Duval
Sylvain Bonhommeau
Victor Illien
AUV
Autonomous Underwater Vehicle
Coastal Ecosystems
Computer Vision
Coral Reef
Coral Reef Habitat
Ecology
Environmental Monitoring
GeoAI
Global Coral Reef Monitoring Network
Indian Ocean
Mapping
Marine Biodiversity
Marine Conservation
Open Science
Photogrammetry
Recif3D
Reef Ecosystem
Remote Sensing
Réunion
Western Indian Ocean
<i>This dataset was collected by an Autonomous Underwater Vehicle in Hermitage, Réunion - 2021-12-01.</i> <br> <br><br>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.<br><br> This dataset is part of larger collection referencing numerous underwater and aerial images <a href="https://doi.org/10.5281/zenodo.11125847" target="_blank">Seatizen Altas</a>. Methods, tools and scientific objectives are also described in a dedicated data paper.<br> <br> This dataset was collected by an Autonomous Underwater Vehicle, Réunion - 2021-12 (project RECIF 3D) <br> This dataset was processed with tools developped by different subsequent projects - 2025-12 (projects PLANCHA, ...) <br> 3D reconstruction and mapping of Reunion coral ecosystems from underwater images.<br> <h2>Survey information</h2> <ul> <li> <strong> Camera</strong>: Prosilica</li> <li> <strong> Number of images</strong>: 140 </li> <li> <strong> Total size</strong>: 1.94 Gb</li> <li> <strong> Flight start</strong>: 2021:12:01 04:47:50 </li> <li> <strong> Flight end</strong>: 2021:12:01 04:50:09</li> <li> <strong> Flight duration</strong>: 0h 2min 19sec</li> <li> <strong> Max depth</strong>: 8.72 m</li> </ul> <h2> Generic folder structure </h2> YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number <br> ├── DCIM : folder to store videos and photos depending on the media collected. <br> ├── 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. <br> │ ├── BASE : files coming from rtk station or any static positioning instrument. <br> │ └── DEVICE : files coming from the device. <br> ├── METADATA : folder with general information files about the session. <br> ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. <br> │ ├── BATHY : output folder for bathymetry raw data extracted from mission logs. <br> │ ├── FRAMES : output folder for georeferenced frames extracted from DCIM videos. <br> │ ├── IA : destination folder for image recognition predictions. <br> │ └── PHOTOGRAMMETRY : destination folder for reconstructed models in photogrammetry. <br> └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot, mission plan etc.). <br> <h2> Software </h2> All the raw data was processed using our <a href="github.com/SeatizenDOI/recif3D-workflow" target="_blank">worflow</a>. <br>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>. <br>Enjoy your data with <a href="https://github.com/SeatizenDOI" target="_blank">SeatizenDOI</a>! <br>
title Underwater images collected by an Autonomous Underwater Vehicle in Hermitage, Réunion - 2021-12-01
topic AUV
Autonomous Underwater Vehicle
Coastal Ecosystems
Computer Vision
Coral Reef
Coral Reef Habitat
Ecology
Environmental Monitoring
GeoAI
Global Coral Reef Monitoring Network
Indian Ocean
Mapping
Marine Biodiversity
Marine Conservation
Open Science
Photogrammetry
Recif3D
Reef Ecosystem
Remote Sensing
Réunion
Western Indian Ocean
url https://doi.org/10.5281/zenodo.18210001