Invasive species represent a big threat for the conservation of the local ecosystems and for the global biodiversity. In fact, they are the second cause of loss of biodiversity in the world. The invasive species can also cause important economic damages and loss if they affect the biological resources and/or the ecological services exploited by humans and also in the human health. In EEUU, invasive species have caused more than 100 M dolars of expenses and in Europe the impact of the aquatic invasive species has been estimated in 2.2 Bilions of euros per year. Invasive algae cause especial fear since they can modify the marine ecosystems and cause great ecological and economic impact. A crucial aspect in the management of the invasive species is an adequate and precise early detection, since it permits to eradicate them with greater success, being the eradication actions more precise and focalized. In this context, new technologies such as Autonomous Underwater Vehicles (AUV) or Autonomous Surface Vehicles (ASV) equipped with cameras are novel tools that provide, automatically and precisely, data of these invasive species with high temporal and spatial resolutions. These techniques permit to obtain 3D maps of the bottom in global coordinates (longitude, latitude and depth), eliminating the risks associated to immersions of a team of divers, augmenting considerably the surveyed region, the obtained data and its repetitiveness. With the aim of identifying automatically the invasive algae Halimeda Incrassata as well as other native species that coexist in the same environment (ej. Cymodocea nodosa), several sampling campaigns using our SPARUS II AUV and our surface vehicle XIROI will be performed to get submarine images of areas colonized with this invasive algae and to generate geolocalized precise mosaics and 3D reconstructions of the environment (sea bottom). These maps will be done in different missions, and will be extremely useful to evaluate the changes in time on the state of the Halimeda and the effectiveness of the eradication actions.

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.

F. Bonin-Font, M. Martín, E. Guerrero, A. Martorell, B. M. Nordfeldt-Fiol, Y. González, J. Máñez, F. Tomás. AUVs for Control of Marine Alien Invasive Species. In IEEE Oceans , Sant Diego/Virtual, 2021.

M. Martín, A. Ruiz, H. Hinz, Y. González. Jellytoring: Real-Time Jellyfish Monitoring Based on Deep Learning Object Detection. In MDPI Sensors, MDPI, vol. 20, no. 6, 2020.

M. Martín, Y. González, A. Ruiz, H. Hinz. The Application of Deep Learning in Marine Sciences. In Book: Deep Learning: Algorithms and Applications, Springer, pp. 193-230, 2020.