When Imagery and Physical Sampling Work Together: Toward an Integrative Methodology of Deep-Sea Image-Based Megafauna Identification

When Imagery and Physical Sampling Work Together: Toward an Integrative Methodology of Deep-Sea Image-Based Megafauna Identification

Imagery has become a key tool for assessing deep-sea megafaunal biodiversity, historically based on physical sampling using fishing gears. Image datasets provide quantitative and repeatable estimates, small-scale spatial patterns and habitat descriptions. However, taxon identification from images is...

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Autores principales: Mélissa Hanafi-Portier, Sarah Samadi, Laure Corbari, Tin-Yam Chan, Wei-Jen Chen, Jhen-Nien Chen, Mao-Ying Lee, Christopher Mah, Thomas Saucède, Catherine Borremans, Karine Olu
Formato: article
Lenguaje:EN
Publicado: Frontiers Media S.A. 2021
Materias:
deep-sea megafauna
image-based identification
biodiversity assessment
identification keys
integrative methodology
towed camera
Science
Q
General. Including nature conservation, geographical distribution
QH1-199.5
Acceso en línea:https://doaj.org/article/e5bf75a143a947169bcb5e381cd1ec72
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https://doaj.org/article/e5bf75a143a947169bcb5e381cd1ec72

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