Type | Illes Balears Local Government | Spanish research project
Duration | 2023 - 2026
Project leader Yolanda González Cid
Collaborators Gabriel Oliver Codina | Francisco Bonin-Font | Antoni Burguera Burguera | Antoni Martorell Torres | Miguel Martín Abadal | Bo Miquel Nordfeldt-Fiol | Caterina Muntaner Gonzalez

DESCRIPTION

This interdisciplinary project incorporates advanced technology (robotics and artificial intelligence) to assess the biodiversity, conservation status, and the role of marine reserves in upholding and enhancing biodiversity and ecosystem services in three crucial habitats along the Balearic coasts: the seagrass meadows of Posidonia oceanica and Cymodocea nodosa, and the forests of Cystoseira.

These habitats offer vital ecosystem services at both local and international levels, including coastal protection, maintenance of water quality, and mitigation of climate change impacts. Furthermore, they provide habitats for a diverse array of species and function as "nursery habitats" for fish, thereby aiding in the sustenance of ecosystem services like fisheries and the preservation of biodiversity.

The study will undertake two complementary approaches to characterize the conservation status of these habitats and their contribution to ecosystem services. This involves comparing data collected on-site by biologists through diving with data obtained from the analysis of automatic images and videos gathered at various locations along the Balearic coast. The acquisition of images and videos will be conducted by divers, autonomous marine vehicles, and stationary submerged stations.

The data acquired through automated analysis of the images, utilizing artificial intelligence, will be compared with the data obtained on-site. This evaluation will enable an assessment of the success, effectiveness, applicability, and reproducibility of this technique for assessing the conservation status and the ability to provide ecosystem services of the underwater forests of the Balearic Islands.

Subproject 1: This segment will present innovative technological solutions based on underwater robotics and deep learning (convolutional neural networks) to automate the observation, detection, and geolocation registration of the habitats under study and their associated species of interest.

Subproject 2: This part will furnish ecological data to validate the data obtained through the use of new technologies and will evaluate the conservation status of the three habitats and their ability to provide ecosystem services.

This work has been partially sponsored and promoted by the Comunitat Autonomade les Illes Balearst hrough the Servei de Recerca i Desenvolupament and the Conselleria de Fons Europeus, Universitat i Cultura and by the European Union-Next Generation EU (BIO/XX). Nevertheless, the views and opinions expressed are solely those of the author or authors, and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the European Commission are to be held responsible

PUBLICATIONS

C. Muntaner, A. Martorell, A. Nadal, V. Pérez, G. Oliver. YOLOv8-based sea urchin detection in ROS for AUV applications. In The 11th International Workshop on Marine Technology, Palma, pp. 79-80, 2024.

C. Muntaner, A. Nadal, M. Martín, Y. González. Automatic deep learning-based pipeline for Mediterranean fish segmentation. In Frontiers in Marine Science, Frontiers , Fabio Fiorentino, vol. 12 - 2025, March, 2025.

F. Bonin-Font, C. Muntaner, B. M. Nordfeldt-Fiol, A. Martorell. Controlling the expansion of Halimeda Incrassata in the Cabrera Natural Park using robots and photo-mosaics. In International Symposium on Monitoring Mediterranean Coastal Areas: problems and measurement techniques, Livorno, 2024.

C. Muntaner, M. Martín, Y. González. A Deep Learning Approach to Estimate Halimeda incrassata Invasive Stage in the Mediterranean Sea. In Marine Science and Engineering, vol. 12, no. 70, pp. 19, December, 2023.


Uso de cookies

Este sitio web utiliza cookies para que usted tenga la mejor experiencia de usuario. Si continúa navegando está dando su consentimiento para la aceptación de las mencionadas cookies y la aceptación de nuestra política de cookies, pinche el enlace para mayor información.

ACEPTAR
Aviso de cookies