155 research outputs found

    Exploring Animal Behavior Through Sound: Volume 1

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    This open-access book empowers its readers to explore the acoustic world of animals. By listening to the sounds of nature, we can study animal behavior, distribution, and demographics; their habitat characteristics and needs; and the effects of noise. Sound recording is an efficient and affordable tool, independent of daylight and weather; and recorders may be left in place for many months at a time, continuously collecting data on animals and their environment. This book builds the skills and knowledge necessary to collect and interpret acoustic data from terrestrial and marine environments. Beginning with a history of sound recording, the chapters provide an overview of off-the-shelf recording equipment and analysis tools (including automated signal detectors and statistical methods); audiometric methods; acoustic terminology, quantities, and units; sound propagation in air and under water; soundscapes of terrestrial and marine habitats; animal acoustic and vibrational communication; echolocation; and the effects of noise. This book will be useful to students and researchers of animal ecology who wish to add acoustics to their toolbox, as well as to environmental managers in industry and government

    Signals and Images in Sea Technologies

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    Life below water is the 14th Sustainable Development Goal (SDG) envisaged by the United Nations and is aimed at conserving and sustainably using the oceans, seas, and marine resources for sustainable development. It is not difficult to argue that signals and image technologies may play an essential role in achieving the foreseen targets linked to SDG 14. Besides increasing the general knowledge of ocean health by means of data analysis, methodologies based on signal and image processing can be helpful in environmental monitoring, in protecting and restoring ecosystems, in finding new sensor technologies for green routing and eco-friendly ships, in providing tools for implementing best practices for sustainable fishing, as well as in defining frameworks and intelligent systems for enforcing sea law and making the sea a safer and more secure place. Imaging is also a key element for the exploration of the underwater world for various scopes, ranging from the predictive maintenance of sub-sea pipelines and other infrastructure projects, to the discovery, documentation, and protection of sunken cultural heritage. The scope of this Special Issue encompasses investigations into techniques and ICT approaches and, in particular, the study and application of signal- and image-based methods and, in turn, exploration of the advantages of their application in the previously mentioned areas

    Framing Cutting-Edge Integrative Deep-Sea Biodiversity Monitoring via Environmental DNA and Optoacoustic Augmented Infrastructures

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    Deep-sea ecosystems are reservoirs of biodiversity that are largely unexplored, but their exploration and biodiscovery are becoming a reality thanks to biotechnological advances (e.g., omics technologies) and their integration in an expanding network of marine infrastructures for the exploration of the seas, such as cabled observatories. While still in its infancy, the application of environmental DNA (eDNA) metabarcoding approaches is revolutionizing marine biodiversity monitoring capability. Indeed, the analysis of eDNA in conjunction with the collection of multidisciplinary optoacoustic and environmental data, can provide a more comprehensive monitoring of deep-sea biodiversity. Here, we describe the potential for acquiring eDNA as a core component for the expanding ecological monitoring capabilities through cabled observatories and their docked Internet Operated Vehicles (IOVs), such as crawlers. Furthermore, we provide a critical overview of four areas of development: (i) Integrating eDNA with optoacoustic imaging; (ii) Development of eDNA repositories and cross-linking with other biodiversity databases; (iii) Artificial Intelligence for eDNA analyses and integration with imaging data; and (iv) Benefits of eDNA augmented observatories for the conservation and sustainable management of deep-sea biodiversity. Finally, we discuss the technical limitations and recommendations for future eDNA monitoring of the deep-sea. It is hoped that this review will frame the future direction of an exciting journey of biodiscovery in remote and yet vulnerable areas of our planet, with the overall aim to understand deep-sea biodiversity and hence manage and protect vital marine resources

    The Adirondack Chronology

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    The Adirondack Chronology is intended to be a useful resource for researchers and others interested in the Adirondacks and Adirondack history.https://digitalworks.union.edu/arlpublications/1000/thumbnail.jp

    Remote Sensing of the Aquatic Environments

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    The book highlights recent research efforts in the monitoring of aquatic districts with remote sensing observations and proximal sensing technology integrated with laboratory measurements. Optical satellite imagery gathered at spatial resolutions down to few meters has been used for quantitative estimations of harmful algal bloom extent and Chl-a mapping, as well as winds and currents from SAR acquisitions. The knowledge and understanding gained from this book can be used for the sustainable management of bodies of water across our planet

    Ocean Noise

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    Scientific and societal concern about the effects of underwater sound on marine ecosystems is growing. While iconic megafauna was of initial concern, more and more taxa are being included. Some countries have joined in multi-national initiatives to measure, monitor and mitigate environmental impacts of ocean noise at large, trans-boundary spatial scales. Approaches to regulating ocean noise change as new scientific evidence becomes available, but may also differ by country. The OCEANOISE conference series has provided a platform for the exchange of scientific results, management approaches, research needs, stakeholder concerns, etc. Attendees have represented various sectors, including academia, offshore industry, defence, NGOs, consultants and government regulators. The published articles in the Special Issue cover a range of topics and applications central to ocean noise

    Framing Cutting-Edge Integrative Deep-Sea Biodiversity Monitoring via Environmental DNA and Optoacoustic Augmented Infrastructures

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    17 pages, 1 figure, 1 tableDeep-sea ecosystems are reservoirs of biodiversity that are largely unexplored, but their exploration and biodiscovery are becoming a reality thanks to biotechnological advances (e.g., omics technologies) and their integration in an expanding network of marine infrastructures for the exploration of the seas, such as cabled observatories. While still in its infancy, the application of environmental DNA (eDNA) metabarcoding approaches is revolutionizing marine biodiversity monitoring capability. Indeed, the analysis of eDNA in conjunction with the collection of multidisciplinary optoacoustic and environmental data, can provide a more comprehensive monitoring of deep-sea biodiversity. Here, we describe the potential for acquiring eDNA as a core component for the expanding ecological monitoring capabilities through cabled observatories and their docked Internet Operated Vehicles (IOVs), such as crawlers. Furthermore, we provide a critical overview of four areas of development: (i) Integrating eDNA with optoacoustic imaging; (ii) Development of eDNA repositories and cross-linking with other biodiversity databases; (iii) Artificial Intelligence for eDNA analyses and integration with imaging data; and (iv) Benefits of eDNA augmented observatories for the conservation and sustainable management of deep-sea biodiversity. Finally, we discuss the technical limitations and recommendations for future eDNA monitoring of the deep-sea. It is hoped that this review will frame the future direction of an exciting journey of biodiscovery in remote and yet vulnerable areas of our planet, with the overall aim to understand deep-sea biodiversity and hence manage and protect vital marine resourcesThis research has been funded within the framework of the following project activities: ARIM (Autonomous Robotic Sea-Floor Infrastructure for Benthopelagic Monitoring; MarTERA ERA-Net Cofound); RESBIO (TEC2017-87861-R; Ministerio de Ciencia, Innovación y Universidades); JERICO-S3: (Horizon 2020; Grant Agreement no. 871153); ENDURUNS (Research Grant Agreement H2020-MG-2018-2019-2020 n.824348); Slovenian Research Agency (Research Core Funding Nos. P1-0237 and P1-0255 and project ARRS-RPROJ-JR-J1-3015). We also profited of the funding from the Spanish Government through the “Severo Ochoa Centre of Excellence” accreditation (CEX2019-000928-S) and Italian Ministry of Education (MIUR) under the “Bando premiale FOE 2015” (nota prot. N. 850, dd. 27 ottobre 2017) with the project EarthCruisers “EARTH’s CRUst Imagery for Investigating Seismicity, Volcanism, and Marine Natural Resources in the Sicilian Offshore”. Ocean Networks Canada was funded through Canada Foundation for Innovation-Major Science Initiative (CFI-MSI) fund 30199Peer reviewe

    Underwater Motion Estimation Based on Acoustic Images and Deep Learning

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    This work develops techniques to estimate the motion of an underwater vehicle by processing acoustic images using deep learning (DL). For this, an underwater sonar simulator based on ray-tracing is designed and implemented. The simulator provides the ground truth data to train and validate proposed techniques. Several DL networks are implemented and compared to identify the most suitable for motion estimation using sonar images. The DL methods showed a much lower computation time and more accurate motion estimates compared to a deterministic algorithm. Further improvements of the DL methods are investigated by preprocessing the data before feeding it to the DL network. One technique converts sonar images into vectors by adding up the pixels in each row. This reduces the size of the DL networks. This technique showed significant reduction in the computation time of up to 10 times compared to techniques that use images. Another preprocessing technique divides the field of view (FoV) of a simulated sonar into four quadrants. An image is generated from each quadrant. This is combined with the vector technique by converting the images into vectors and grouping them together as the input of the DL network. The FoV division approach showed a high accuracy compared to using the whole FoV or different portions of it. Another motion estimation method presented in this work is enabled by full-duplex operation and rather than using images, it is based on DL analysis of time variation of complex-valued channel impulse responses. This technique can significantly reduce the acoustic hardware and processing complexity of the DL network and obtain a higher motion estimation accuracy, compared with techniques based on the processing of sonar images. The navigation accuracy of all the techniques is further illustrated by examples of estimation of complex trajectories using simulated and real data

    Deep learning for internet of underwater things and ocean data analytics

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    The Internet of Underwater Things (IoUT) is an emerging technological ecosystem developed for connecting objects in maritime and underwater environments. IoUT technologies are empowered by an extreme number of deployed sensors and actuators. In this thesis, multiple IoUT sensory data are augmented with machine intelligence for forecasting purposes
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