Seatizen Atlas: a collaborative dataset of underwater and aerial marine imagery.

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2025-01-14 DOI:10.1038/s41597-024-04267-z
Matteo Contini, Victor Illien, Mohan Julien, Mervyn Ravitchandirane, Victor Russias, Arthur Lazennec, Thomas Chevrier, Cam Ly Rintz, Léanne Carpentier, Pierre Gogendeau, César Leblanc, Serge Bernard, Alexandre Boyer, Justine Talpaert Daudon, Sylvain Poulain, Julien Barde, Alexis Joly, Sylvain Bonhommeau
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Abstract

Citizen Science initiatives have a worldwide impact on environmental research by providing data at a global scale and high resolution. Mapping marine biodiversity remains a key challenge to which citizen initiatives can contribute. Here we describe a dataset made of both underwater and aerial imagery collected in shallow tropical coastal areas by using various low cost platforms operated either by citizens or researchers. This dataset is regularly updated and contains >1.6 M images from the Southwest Indian Ocean. Most of images are geolocated, and some are annotated with 51 distinct classes (e.g. fauna, and habitats) to train AI models. The quality of these photos taken by action cameras along the trajectories of different platforms, is highly heterogeneous (due to varying speed, depth, turbidity, and perspectives) and well reflects the challenges of underwater image recognition. Data discovery and access rely on DOI assignment while data interoperability and reuse is ensured by complying with widely used community standards. The open-source data workflow is provided to ease contributions from anyone collecting pictures.

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Seatizen Atlas:水下和空中海洋图像的协作数据集。
公民科学计划通过提供全球范围和高分辨率的数据,对环境研究产生了全球性的影响。绘制海洋生物多样性地图仍然是公民倡议可以作出贡献的一项关键挑战。在这里,我们描述了一个数据集,该数据集由在热带沿海浅层地区收集的水下和空中图像组成,这些图像是通过由公民或研究人员操作的各种低成本平台收集的。该数据集定期更新,包含来自西南印度洋的160万张图像。大多数图像都是地理定位的,有些图像被标注为51个不同的类别(例如动物群和栖息地),以训练AI模型。这些由运动相机沿着不同平台的轨迹拍摄的照片的质量是高度异构的(由于不同的速度、深度、浊度和视角),很好地反映了水下图像识别的挑战。数据发现和访问依赖于DOI分配,而数据互操作性和重用则通过遵守广泛使用的社区标准来确保。提供开源数据工作流是为了方便任何人收集图片。
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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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