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Journal articles on the topic 'Marine drone'
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1
Kelaher, Brendan P., Victor M. Peddemors, Brent Hoade, Andrew P. Colefax, and Paul A. Butcher. "Comparison of sampling precision for nearshore marine wildlife using unmanned and manned aerial surveys." Journal of Unmanned Vehicle Systems 8, no. 1 (March 1, 2020): 30–43. http://dx.doi.org/10.1139/juvs-2018-0023.
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Aerial surveys of large marine wildlife in nearshore areas can support management actions to ensure conservation of this megafauna. While most aerial surveys of marine wildlife have been carried out using manned aircraft, unmanned aerial systems (commonly known as drones) are being increasingly used. Here, we compare the relative accuracy and precision of marine wildlife surveys from a multirotor drone and a manned helicopter for the first time. At two locations on the east coast of Australia, we simultaneously surveyed sharks (including white sharks, Carcharodon carcharias), dolphins, rays, and sea turtles in nearshore coastal areas using a multirotor drone (DJI Inspire I) and a helicopter (Robinson 44 Clipper II) over 26 separate flights. Sampling included the real-time quantification of marine wildlife by an observer in the helicopter and the pilot of the drone. The video feed from the drone was then later re-sampled in the laboratory. Of the three methods, post-hoc analysis of drone video footage is likely to provide the most accurate and precise estimates of marine wildlife in nearshore areas. When real-time data are required (e.g., for shark-risk mitigation), manned helicopters (over larger stretches of coast) and drones (across localised beaches) will both be useful.
2
Raoult, Vincent, Andrew P. Colefax, Blake M. Allan, Daniele Cagnazzi, Nataly Castelblanco-Martínez, Daniel Ierodiaconou, David W. Johnston, et al. "Operational Protocols for the Use of Drones in Marine Animal Research." Drones 4, no. 4 (September 25, 2020): 64. http://dx.doi.org/10.3390/drones4040064.
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The use of drones to study marine animals shows promise for the examination of numerous aspects of their ecology, behaviour, health and movement patterns. However, the responses of some marine phyla to the presence of drones varies broadly, as do the general operational protocols used to study them. Inconsistent methodological approaches could lead to difficulties comparing studies and can call into question the repeatability of research. This review draws on current literature and researchers with a wealth of practical experience to outline the idiosyncrasies of studying various marine taxa with drones. We also outline current best practice for drone operation in marine environments based on the literature and our practical experience in the field. The protocols outlined herein will be of use to researchers interested in incorporating drones as a tool into their research on marine animals and will help form consistent approaches for drone-based studies in the future.
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Pham, Duc-Anh, and Seung-Hun Han. "Design of Combined Neural Network and Fuzzy Logic Controller for Marine Rescue Drone Trajectory-Tracking." Journal of Marine Science and Engineering 10, no. 11 (November 10, 2022): 1716. http://dx.doi.org/10.3390/jmse10111716.
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In recent years, the research on drones has increased rapidly because of its high applicability in many fields and its great development potential. In the maritime sector too, especially marine rescue, a Drone with a compact size and fast flight speed is an effective solution in search and surveillance, giving quick results and being very convenient. When operating at sea, marine rescue drones are often affected by the environment, especially wind, which leads to turbulence that causes the drone to deviate from its predetermined flight trajectory. To overcome the above problem, the author has proposed the application of a Neural-Fuzzy controller for unmanned marine rescue aircraft presented in this paper introduces a controller that combines neural networks and fuzzy controllers that enhance the efficiency of the drone’s trajectory tracking. The paper presents the mathematics of a quadcopter described by the Newton-Euler equations. Presentation on stable flight control and trajectory control of marine rescue drones. In this paper, Matlab/Simulink is used to describe the operation of the Drone, and the characteristics obtained after using the simulation are used to compare, test, and analyze the system. The obtained results show that the Neural-Fuzzy controller is much more sensitive, more resistant to turbulence, and can be used on different sizes, weights, and configurations of drones without adjusting PID gain.
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Mocanu, Vlad. "Charging floating bases for marine unmanned aerial drone." Scientific Bulletin of Naval Academy XXIII, no. 1 (July 15, 2020): 116–21. http://dx.doi.org/10.21279/1454-864x-20-i1-015.
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In this paper, the authors present new ways of using drones in the marine and offshore environments. The article includes the presentation of the main constructive electrical elements of a marine floating buoy, which play the role of charging base for an unmanned aerial drone. Also, are highlighted the main losses of the system’s components, what should have been taken into account when choosing the size of such an independent energy source, as well as the main steps for energy source design.
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Lim, Jae-Jun, Dae-Won Kim, Woon-Hee Hong, Min Kim, Dong-Hoon Lee, Sun-Young Kim, and Jae-Hoon Jeong. "Application of Convolutional Neural Network (CNN) to Recognize Ship Structures." Sensors 22, no. 10 (May 18, 2022): 3824. http://dx.doi.org/10.3390/s22103824.
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The purpose of this paper is to study the recognition of ships and their structures to improve the safety of drone operations engaged in shore-to-ship drone delivery service. This study has developed a system that can distinguish between ships and their structures by using a convolutional neural network (CNN). First, the dataset of the Marine Traffic Management Net is described and CNN’s object sensing based on the Detectron2 platform is discussed. There will also be a description of the experiment and performance. In addition, this study has been conducted based on actual drone delivery operations—the first air delivery service by drones in Korea.
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Barreto, Jonathas, Luciano Cajaíba, João Batista Teixeira, Lorena Nascimento, Amanda Giacomo, Nelson Barcelos, Ticiana Fettermann, and Agnaldo Martins. "Drone-Monitoring: Improving the Detectability of Threatened Marine Megafauna." Drones 5, no. 1 (February 20, 2021): 14. http://dx.doi.org/10.3390/drones5010014.
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Unmanned aerial vehicles (UAVs; or drones) are an emerging tool to provide a safer, cheaper, and quieter alternative to traditional methods of studying marine megafauna in a natural environment. The UFES Nectology Laboratory team developed a drone-monitoring to assess the impacts on megafauna related to the Fundão dam mining tailings disaster in the Southeast Brazilian coast. We have developed a systematic pattern to optimize the available resources by covering the largest possible area. The fauna observer can monitor the environment from a privileged angle with virtual reality and subsequently analyzes each video captured in 4k, allowing to deepening behavioral ecology knowledge. Applying the drone-monitoring method, we have observed an increasing detectability by adjusting the camera angle, height, orientation, and speed of the UAV; which saved time and resources for monitoring turtles, sea birds, large fish, and especially small cetaceans efficiently and comparably.
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Jeon, I., S. Ham, J. Cheon, A. M. Klimkowska, H. Kim, K. Choi, and I. Lee. "A REAL-TIME DRONE MAPPING PLATFORM FOR MARINE SURVEILLANCE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 4, 2019): 385–91. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-385-2019.
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<p><strong>Abstract.</strong> Marine incidents have caused serious casualties and damaged on property, and situational awareness and actions are needed to reduce further extensive damage for marine surveillance. The importance of an attempt for maritime monitoring using UAV has been raised, and a platform should be prepared to respond immediately to urgent situations. In this research, a real-time drone image mapping platform is proposed for marine surveillance that receives marine images acquired and transmitted by drones and processes them in real time. The platform proposed in this study is divided into 1) UAV System, 2) Real-time image processing, 3) Visualization. UAV system transfers data from a drone to the ground stations. Real-time image processing module generates individual orthophotos followed by directly georeferencing in real time and detecting ships on the orthophotos. Visualization module enables to visualize the orthophotos. The overall mapping time of 3.26 seconds on average was verified for processing image mapping, and ship detection time for a single image was estimated to be within about 1 second, which corresponds to an environment in which an emergency must be handled. In conclusion, a real-time drone mapping platform that is introduced in this study can be evaluated as being available for maritime monitoring that requires swift responses.</p>
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Joyce, K. E., S. Duce, S. M. Leahy, J. Leon, and S. W. Maier. "Principles and practice of acquiring drone-based image data in marine environments." Marine and Freshwater Research 70, no. 7 (2019): 952. http://dx.doi.org/10.1071/mf17380.
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With almost limitless applications across marine and freshwater environments, the number of people using, and wanting to use, remotely piloted aircraft systems (or drones) is increasing exponentially. However, successfully using drones for data collection and mapping is often preceded by hours of researching drone capabilities and functionality followed by numerous limited-success flights as users tailor their approach to data collection through trial and error. Working over water can be particularly complex and the published research using drones rarely documents the methodology and practical information in sufficient detail to allow others, with little remote pilot experience, to replicate them or to learn from their mistakes. This can be frustrating and expensive, particularly when working in remote locations where the window of access is small. The aim of this paper is to provide a practical guide to drone-based data acquisition considerations. We hope to minimise the amount of trial and error required to obtain high-quality, map-ready data by outlining the principles and practice of data collection using drones, particularly in marine and freshwater environments. Importantly, our recommendations are grounded in remote sensing and photogrammetry theory so that the data collected are appropriate for making measurements and conducting quantitative data analysis.
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Rowe, Claire E., Will F. Figueira, Brendan P. Kelaher, Anna Giles, Lea T. Mamo, Shane T. Ahyong, and Stephen J. Keable. "Evaluating the effectiveness of drones for quantifying invasive upside-down jellyfish (Cassiopea sp.) in Lake Macquarie, Australia." PLOS ONE 17, no. 1 (January 19, 2022): e0262721. http://dx.doi.org/10.1371/journal.pone.0262721.
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Upside-down jellyfish (Cassiopea sp.) are mostly sedentary, benthic jellyfish that have invaded estuarine ecosystems around the world. Monitoring the spread of this invasive jellyfish must contend with high spatial and temporal variability in abundance of individuals, especially around their invasion front. Here, we evaluated the utility of drones to survey invasive Cassiopea in a coastal lake on the east coast of Australia. To assess the efficacy of a drone-based methodology, we compared the densities and counts of Cassiopea from drone observations to conventional boat-based observations and evaluated cost and time efficiency of these methods. We showed that there was no significant difference in Cassiopea density measured by drones compared to boat-based methods along the same transects. However, abundance estimates of Cassiopea derived from scaling-up transect densities were over-inflated by 319% for drones and 178% for boats, compared to drone-based counts of the whole site. Although conventional boat-based survey techniques were cost-efficient in the short-term, we recommend doing whole-of-site counts using drones. This is because it provides a time-saving and precise technique for long-term monitoring of the spatio-temporally dynamic invasion front of Cassiopea in coastal lakes and other sheltered marine habitats with relatively clear water.
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Kelaher, Brendan P., Andrew P. Colefax, Alejandro Tagliafico, Melanie J. Bishop, Anna Giles, and Paul A. Butcher. "Assessing variation in assemblages of large marine fauna off ocean beaches using drones." Marine and Freshwater Research 71, no. 1 (2020): 68. http://dx.doi.org/10.1071/mf18375.
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The turbulent waters off ocean beaches provide habitat for large marine fauna, including dolphins, sharks, rays, turtles and game fish. Although, historically, these assemblages have proven difficult to quantify, we used a new drone-based approach to assess spatial and temporal variation in assemblages of large marine fauna off four exposed beaches in New South Wales, Australia. In total, 4388 individual large marine animals were identified from 216 drone flights. The most common taxa, bottlenose dolphins (Tursiops spp.) and Australian cownose rays (Rhinoptera neglecta), occurred in 25.5 and 19.9% of flights respectively. White (Carcharodon carcharias), bull (Carcharhinus leucas) and other whaler (Carcharhinus spp.) sharks were observed in <1% of flights. There was significant variation in the structure of assemblages of large fauna among beaches, with those adjacent to riverine estuaries having greater richness and abundance of wildlife. Overall, drone surveys were successful in documenting the spatio-temporal dynamics of an impressive suite of large marine fauna. We contend that emerging drone technology can make a valuable contribution to the ecological information required to ensure the long-term sustainability of sandy-beach ecosystems and associated marine wildlife.
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Burke, McWhirter, Veitch-Michaelis, McAree, Pointon, Wich, and Longmore. "Requirements and Limitations of Thermal Drones for Effective Search and Rescue in Marine and Coastal Areas." Drones 3, no. 4 (October 14, 2019): 78. http://dx.doi.org/10.3390/drones3040078.
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Search and rescue (SAR) is a vital line of defense against unnecessary loss of life. However,in a potentially hazardous environment, it is important to balance the risks associated with SARaction. Drones have the potential to help with the efficiency, success rate and safety of SAR operationsas they can cover large or hard to access areas quickly. The addition of thermal cameras to the dronesprovides the potential for automated and reliable detection of people in need of rescue. We performeda pilot study with a thermal-equipped drone for SAR applications in Morecambe Bay. In a varietyof realistic SAR scenarios, we found that we could detect humans who would be in need of rescue,both by the naked eye and by a simple automated method. We explore the current advantages andlimitations of thermal drone systems, and outline the future path to a useful system for deploymentin real-life SAR.
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Hamad, Idrissa Yussuf, Peter Anton Upadhyay Staehr, Michael Bo Rasmussen, and Mohammed Sheikh. "Drone-Based Characterization of Seagrass Habitats in the Tropical Waters of Zanzibar." Remote Sensing 14, no. 3 (January 31, 2022): 680. http://dx.doi.org/10.3390/rs14030680.
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Unmanned automatic systems (UAS) are increasingly being applied as an alternative to more costly time-consuming traditional methods for mapping and monitoring marine shallow-water ecosystems. Here, we demonstrate the utility of combining aerial drones with in situ imagery to characterize the habitat conditions of nine shallow-water seagrass-dominated areas on Unguja Island, Zanzibar. We applied object-based image analysis and a maximum likelihood algorithm on the drone images to derive habitat cover maps and important seagrass habitat parameters: the habitat composition; the seagrass species; the horizontal- and depth-percent covers, and the seascape fragmentation. We mapped nine sites covering 724 ha, categorized into seagrasses (55%), bare sediment (31%), corals (9%), and macroalgae (5%). An average of six seagrass species were found, and 20% of the nine sites were categorized as “dense cover” (40–70%). We achieved high map accuracy for the habitat types (87%), seagrass (80%), and seagrass species (76%). In all nine sites, we observed clear decreases in the seagrass covers with depths ranging from 30% at 1–2 m, to 1.6% at a 4–5 m depth. The depth dependency varied significantly among the seagrass species. Areas associated with low seagrass cover also had a more fragmented distribution pattern, with scattered seagrass populations. The seagrass cover was correlated negatively (r2 = 0.9, p < 0.01) with sea urchins. A multivariate analysis of the similarity (ANOSIM) of the biotic features, derived from the drone and in situ data, suggested that the nine sites could be organized into three significantly different coastal habitat types. This study demonstrates the high robustness of drones for characterizing complex seagrass habitat conditions in tropical waters. We recommend adopting drones, combined with in situ photos, for establishing a suite of important data relevant for marine ecosystem monitoring in the Western Indian Ocean (WIO).
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Andriolo, Umberto, Odei Garcia-Garin, Morgana Vighi, Asunción Borrell, and Gil Gonçalves. "Beached and Floating Litter Surveys by Unmanned Aerial Vehicles: Operational Analogies and Differences." Remote Sensing 14, no. 6 (March 9, 2022): 1336. http://dx.doi.org/10.3390/rs14061336.
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The abundance of litter pollution in the marine environment has been increasing globally. Remote sensing techniques are valuable tools to advance knowledge on litter abundance, distribution and dynamics. Images collected by Unmanned Aerial Vehicles (UAV, aka drones) are highly efficient to map and monitor local beached (BL) and floating (FL) marine litter items. In this work, the operational insights to carry out both BL and FL surveys using UAVs are detailly described. In particular, flight planning and deployment, along with image products processing and analysis, are reported and compared. Furthermore, analogies and differences between UAV-based BL and FL mapping are discussed, with focus on the challenges related to BL and FL item detection and recognition. Given the efficiency of UAV to map BL and FL, this remote sensing technique can replace traditional methods for litter monitoring, further improving the knowledge of marine litter dynamics in the marine environment. This communication aims at helping researchers in planning and performing optimized drone-based BL and FL surveys.
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Mitchell, Jonathan D., Tracey B. Scott-Holland, and Paul A. Butcher. "Factors Affecting Shark Detection from Drone Patrols in Southeast Queensland, Eastern Australia." Biology 11, no. 11 (October 23, 2022): 1552. http://dx.doi.org/10.3390/biology11111552.
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Drones enable the monitoring for sharks in real-time, enhancing the safety of ocean users with minimal impact on marine life. Yet, the effectiveness of drones for detecting sharks (especially potentially dangerous sharks; i.e., white shark, tiger shark, bull shark) has not yet been tested at Queensland beaches. To determine effectiveness, it is necessary to understand how environmental and operational factors affect the ability of drones to detect sharks. To assess this, we utilised data from the Queensland SharkSmart drone trial, which operated at five southeast Queensland beaches for 12 months in 2020–2021. The trial conducted 3369 flights, covering 1348 km and sighting 174 sharks (48 of which were >2 m in length). Of these, eight bull sharks and one white shark were detected, leading to four beach evacuations. The shark sighting rate was 3% when averaged across all beaches, with North Stradbroke Island (NSI) having the highest sighting rate (17.9%) and Coolum North the lowest (0%). Drone pilots were able to differentiate between key shark species, including white, bull and whaler sharks, and estimate total length of the sharks. Statistical analysis indicated that location, the sighting of other fauna, season and flight number (proxy for time of day) influenced the probability of sighting sharks.
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Pirotta, Vanessa, David P. Hocking, Jason Iggleden, and Robert Harcourt. "Drone Observations of Marine Life and Human–Wildlife Interactions off Sydney, Australia." Drones 6, no. 3 (March 11, 2022): 75. http://dx.doi.org/10.3390/drones6030075.
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Drones have become popular with the general public for viewing and filming marine life. One amateur enthusiast platform, DroneSharkApp, films marine life in the waters off Sydney, Australia year-round and posts their observations on social media. The drone observations include the behaviours of a variety of coastal marine wildlife species, including sharks, rays, fur seals, dolphins and fish, as well as migratory species such as migrating humpback whales. Given the extensive effort and multiple recordings of the presence, behaviour and interactions of various species with humans provided by DroneSharkApp, we explored its utility for providing biologically meaningful observations of marine wildlife. Using social media posts from the DroneSharkApp Instagram page, a total of 678 wildlife videos were assessed from 432 days of observation collected by a single observer. This included 94 feeding behaviours or events for fur seals (n = 58) and dolphins (n = 33), two feeding events for white sharks and one feeding event for a humpback whale. DroneSharkApp documented 101 interactions with sharks and humans (swimmers and surfers), demonstrating the frequent, mainly innocuous human–shark overlap off some of Australia’s busiest beaches. Finally, DroneSharkApp provided multiple observations of humpback and dwarf minke whales with calves travelling north, indicating calving occurring well south of traditional northern Queensland breeding waters. Collaboration between scientists and citizen scientists such as those involved with DroneSharkApp can greatly and quantitatively increase the biological understanding of marine wildlife data.
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Oleksyn, Semonn, Louise Tosetto, Vincent Raoult, Karen E. Joyce, and Jane E. Williamson. "Going Batty: The Challenges and Opportunities of Using Drones to Monitor the Behaviour and Habitat Use of Rays." Drones 5, no. 1 (February 2, 2021): 12. http://dx.doi.org/10.3390/drones5010012.
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The way an animal behaves in its habitat provides insight into its ecological role. As such, collecting robust, accurate datasets in a time-efficient manner is an ever-present pressure for the field of behavioural ecology. Faced with the shortcomings and physical limitations of traditional ground-based data collection techniques, particularly in marine studies, drones offer a low-cost and efficient approach for collecting data in a range of coastal environments. Despite drones being widely used to monitor a range of marine animals, they currently remain underutilised in ray research. The innovative application of drones in environmental and ecological studies has presented novel opportunities in animal observation and habitat assessment, although this emerging field faces substantial challenges. As we consider the possibility to monitor rays using drones, we face challenges related to local aviation regulations, the weather and environment, as well as sensor and platform limitations. Promising solutions continue to be developed, however, growing the potential for drone-based monitoring of behaviour and habitat use of rays. While the barriers to enter this field may appear daunting for researchers with little experience with drones, the technology is becoming increasingly accessible, helping ray researchers obtain a wide range of highly useful data.
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Colefax, Andrew P., Paul A. Butcher, Daniel E. Pagendam, and Brendan P. Kelaher. "Reliability of marine faunal detections in drone-based monitoring." Ocean & Coastal Management 174 (May 2019): 108–15. http://dx.doi.org/10.1016/j.ocecoaman.2019.03.008.
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Siswantoro, Nurhadi, Trika Pitana, Muhammad Badrus Zaman, Dwi Priyanta, and Hari Prastowo. "Pelatihan Pemanfaatan Drone dan Aplikasi Digital untuk Menunjang Sektor Agro Maritim di Kabupaten Tulungagung." SEWAGATI 6, no. 1 (February 13, 2022): 116–26. http://dx.doi.org/10.12962/j26139960.v6i1.197.
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Budidaya perikanan tawar di Kabupaten Tulungagung merupakan salah satu penghasil produksi ikan tawar terbesar di Jawa Timur. Produksi perikanan air tawar di Kabupaten Tulungagung terbagi menjadi ikan hias dan konsumsi, seperti: lele, gurami, patin dan nila. Kabupaten Tulungagung dengan potensi perikanan tawar memerlukan teknologi digital informasi dan inovasi dalam mengelola sumber daya perikanan. Penggunaan teknologi seperti drone juga dapat dimanfaatkan untuk menunjang pemasaran digital maupun inovasi pada pemberian pakan ikan secara otomatis. Penggunaan drone di bidang digital marketing dapat memberikan banyak kelebihan khususnya dalam efisiensi waktu. Kelebihan drone adalah sebagai berikut, fleksibilitas sangat tinggi, menghasilkan resolusi sangat tinggi, automatic/manual operation sesuai kebutuhan. Untuk inovasi pemberian pakan ikan secara otomatis, drone buatan Laboratorium Digital Marine Operation and Mainenance ITS memiliki kemampuan jangkauan remotely 1 kilometer dan kemampuan terbang selama 20 menit, serta membawa beban 4 kilogram. Pada simulasi pemberian pakan ikan, drone diterbangan dengan membawa pakan seberat 1 kilogram dan secara remote pakan otomatis dituangkan ke kolam. Hasilnya ikan tidak merasa terganggu dengan suara drone dan langsung menyambar pakan ikan yang jatuh dari atas drone. Simulasi pemanfaatan drone untuk pemberian pakan ikan, memberikan wawasan dan pandangan terhadap petani ikan bahwa saat ini teknologi agro maritim harus berinovasi untuk meningkatkan produktifitas perikanan.
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Fish, Adam. "Seadrones: Sensing Oceancultures." Journal of Environmental Media 1, no. 2 (July 1, 2020): 139–44. http://dx.doi.org/10.1386/jem_00012_1.
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Drones are airborne sensing technologies that transform how we see from above and respond to crises on the ground. Nowhere does the drone revolution have more potential applications than in Australia’s ocean sciences. Drones give oceanographers fast, safe, mobile, high-definition and affordable ways of seeing, identifying and monitoring endangered marine species such as sharks, whales and corals. They are used in Australia to document the rate of coral death in the Great Barrier Reef, the health of humpback whales and the presence of great white sharks near swimmers. However, scientific data collected by drones has, thus far, failed to translate into effective environmental policy. Understanding how seeing informs science ‐ and why or why not science influences policy ‐ has serious consequences for how Australia’s oceans are sustainably managed. This is not only important for the survival of marine species but also renovates central debates about sensing and political action within science and technology studies. I will briefly outline a research agenda that would hope to make contributions to the seeing and management of the sea and advance our knowledge of seacultures ‐ the convergence of the sea and the culture.
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Choi, Seo Yeol, Hyeon Jung Kim, Min Ho Seo, and Ho Young Soh. "Density Estimation of Nemopilema nomurai (Scyphozoa, Rhizostomeae) Using a Drone." Journal of the Indian Society of Remote Sensing 49, no. 7 (March 22, 2021): 1727–32. http://dx.doi.org/10.1007/s12524-021-01347-0.
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AbstractResearch to understand the distribution and density of jellyfish is actively being conducted using training ships, but this is hindered by the high cost of manpower and the limitations of the irradiation area. Unmanned aerial vehicles (UAVs or drones), however, provide cost-effective means for assessing marine animal populations. Therefore, we tested the application of UAVs in estimating jellyfish density and probed the altitude-dependent suitability of these devices. We analyzed images obtained by a drone as well as by manual counting and used ImageJ to measure the density of Nemopilema nomurai off Sang-Chuja Island, Jeju, South Korea. Analysis of the image obtained at altitudes of 5–120 m allowed for the identification of 2–173 individuals, while 1.49–9.09 individuals were identified per 100 m2. Jellyfish density data measured by manual count and by ImageJ did not show any difference below 90 m; however, a difference was presented at altitudes of 100 m (98%) and 120 m (95%). These results demonstrate the potential of drones for jellyfish monitoring and recommend an optimal altitude for observation.
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Raoult, Vincent, Louise Tosetto, and Jane Williamson. "Drone-Based High-Resolution Tracking of Aquatic Vertebrates." Drones 2, no. 4 (November 8, 2018): 37. http://dx.doi.org/10.3390/drones2040037.
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Determining the small-scale movement patterns of marine vertebrates usually requires invasive active acoustic tagging or in-water monitoring, with the inherent behavioural impacts of those techniques. In addition, these techniques rarely allow direct continuous behavioural assessments or the recording of environmental interactions, especially for highly mobile species. Here, we trial a novel method of assessing small-scale movement patterns of marine vertebrates using an unmanned aerial vehicle that could complement longer-term tracking approaches. This approach is unlikely to have behavioural impacts and provides high accuracy and high frequency location data (10 Hz), while subsequently allowing quantitative trajectory analysis. Unmanned aerial vehicle tracking is also relatively low cost compared to single-use acoustic and GPS tags. We tracked 14 sharks for up to 10 min in a shallow lagoon of Heron Island, Australia. Trajectory analysis revealed that Epaulette sharks (Hemiscyllium ocellatum) displayed sinusoidal movement patterns, while Blacktip Reef Sharks (Carcharhinus melanopterus) had more linear trajectories that were similar to those of a Lemon shark (Negaprion acutidens). Individual shark trajectory patterns and movement speeds were highly variable. Results indicate that Epaulette sharks may be more mobile during diurnal low tides than previously thought. The approach presented here allows the movements and behaviours of marine vertebrates to be analysed at resolutions not previously possible without complex and expensive acoustic arrays. This method would be useful to assess the habitat use and behaviours of sharks and rays in shallow water environments, where they are most likely to interact with humans.
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Man, Dong-Woo, and Hyun-Sik Kim. "Mechanism Development and Heading Control of Catamaran-type Sail Drone." Journal of Ocean Engineering and Technology 35, no. 5 (October 31, 2021): 360–68. http://dx.doi.org/10.26748/ksoe.2021.062.
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The need for energy harvesting in marine environments is gradually increasing owing to the energy limitation of marine robots. To address this problem, a catamaran-type sail drone (CSD), which can harvest marine energies such as wind and solar, was proposed in a previous study. However, it was designed and manufactured without considering the stability, optimal hull-form, and maintenance. To resolve these problems, a CSD with two keels, a performance estimator, V-shape hulls, and modularized components is proposed and its mechanism is developed in this study. To verify the performance of the CSD, the performance estimation using smoothed-particle hydrodynamics (SPH) and the heading control using fuzzy logic controller (FLC) are performed. Simulation results show the attitude stability of the CSD and the experimental results show the straight path of the CSD according to wind conditions. Therefore, the CSD has potential applications as an energy harvesting system.
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Mitrofanov, D. V., and N. V. Budnikova. "The content of decenoic acids in drone brood preparations and combined preparations based on it." Biomics 12, no. 3 (2020): 389–93. http://dx.doi.org/10.31301/2221-6197.bmcs.2020-29.
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The drone brood contains a large number of substances with antioxidant activity. These substances require stabilization and strict adherence to storage conditions. Among these substances are unique decenoic acids, the content of which is an indicator of the quality of drone brood and products based on it. The ability of drone brood to reduce the manifestations of oxidative stress is shown. There are dietary supplements for food and drugs based on drone brood, which are used for a wide range of diseases. Together with drone brood, chitosan-containing products, propolis, royal jelly can be used. They enrich the composition with their own biologically active substances and affect the preservation of the biologically active substances of the drone brood. Promising are the products containing, in addition to the drone brood, a chitin-chitosan-melanin complex from bees, propolis, royal jelly. The chitin-chitosan-melanin complex in the amount of 5% in the composition of the adsorbent practically does not affect the preservation of decenic acids, while in the amount of 2% and 10% it somewhat worsens. The acid-soluble and water-soluble chitosan of marine crustaceans significantly worsens the preservation of decenoic acids in the product. Drone brood with royal jelly demonstrates a rather high content of decenoic acids. When propolis is introduced into the composition of the product, the content of decenoic acids increases according to the content of propolis.
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Merlino, Silvia, Marco Paterni, Marina Locritani, Umberto Andriolo, Gil Gonçalves, and Luciano Massetti. "Citizen Science for Marine Litter Detection and Classification on Unmanned Aerial Vehicle Images." Water 13, no. 23 (November 25, 2021): 3349. http://dx.doi.org/10.3390/w13233349.
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Unmanned aerial vehicles (UAV, aka drones) are being used for mapping macro-litter in the environment. As drone images require a manual processing task for detecting marine litter, it is of interest to evaluate the accuracy of non-expert citizen science operators (CSO) in performing this task. Students from Italian secondary schools (in this work, the CSO) were invited to identify, mark, and classify stranded litter items on a UAV orthophoto collected on an Italian beach. A specific training program and working tools were developed for the aim. The comparison with the standard in situ visual census survey returned a general underestimation (50%) of items. However, marine litter bulk categorisation was fairly in agreement with the in situ survey, especially for sources classification. The concordance level among CSO ranged between 60% and 91%, depending on the item properties considered (type, material, and colour). As the assessment accuracy was in line with previous works developed by experts, remote detection of marine litter on UAV images can be improved through citizen science programs, upon an appropriate training plan and provision of specific tools.
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Dickson, Liam C. D., Stuart R. B. Negus, Christophe Eizaguirre, Kostas A. Katselidis, and Gail Schofield. "Aerial Drone Surveys Reveal the Efficacy of a Protected Area Network for Marine Megafauna and the Value of Sea Turtles as Umbrella Species." Drones 6, no. 10 (October 7, 2022): 291. http://dx.doi.org/10.3390/drones6100291.
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Quantifying the capacity of protected area networks to shield multiple marine megafauna with diverse life histories is complicated, as many species are wide-ranging, requiring varied monitoring approaches. Yet, such information is needed to identify and assess the potential use of umbrella species and to plan how best to enhance conservation strategies. Here, we evaluated the effectiveness of part of the European Natura 2000 protected area network (western Greece) for marine megafauna and whether loggerhead sea turtles are viable umbrella species in this coastal region. We systematically surveyed inside and outside coastal marine protected areas (MPAs) at a regional scale using aerial drones (18,505 animal records) and combined them with distribution data from published datasets (tracking, sightings, strandings) of sea turtles, elasmobranchs, cetaceans and pinnipeds. MPAs covered 56% of the surveyed coastline (~1500 km). There was just a 22% overlap in the distributions of the four groups from aerial drone and other datasets, demonstrating the value of combining different approaches to improve records of coastal area use for effective management. All four taxonomic groups were more likely to be detected inside coastal MPAs than outside, confirming sufficient habitat diversity despite varied life history traits. Coastal habitats frequented by loggerhead turtles during breeding/non-breeding periods combined overlapped with 76% of areas used by the other three groups, supporting their potential use as an umbrella species. In conclusion, this study showed that aerial drones can be readily combined with other monitoring approaches in coastal areas to enhance the management of marine megafauna in protected area networks and to identify the efficacy of umbrella species.
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Duan, Zheng, Ying Li, Xun Wang, Jinlei Wang, Mikkel Brydegaard, Guangyu Zhao, and Sune Svanberg. "Drone-Based Fluorescence Lidar Systems for Vegetation and Marine Environment Monitoring." EPJ Web of Conferences 237 (2020): 07013. http://dx.doi.org/10.1051/epjconf/202023707013.
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We have developed two different types of drone-based fluorescence lidar systems for vegetation and marine environment monitoring, both based on violet CW diode lasers. An inelastic hyperspectral Scheimpflug lidar system was used for vegetation profiling combined with fluorescence spectral recordings. A light-weight fluorosensor set for fixed-height recordings was employed for monitoring of marine environments, featuring water Raman signals, algal chlorophyll and strong oil spill fluorescence.
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Moustanir, Mohamed, Karim Benkirane, Adil Sayouti, and Hicham Medromi. "Four propellers submarine drone modelling in a real environment." International Journal of Power Electronics and Drive Systems (IJPEDS) 12, no. 4 (December 1, 2021): 1966. http://dx.doi.org/10.11591/ijpeds.v12.i4.pp1966-1977.
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<span lang="EN-US">In order to reduce the hydrodynamic dampers and mechanical elements as rudders, we have in our previous publications proposed our architectural solution of an ROV with only four thrusters without rudders or diving bars. In the results we have justified the choice of the arrangement of the thrusters. Also, we have started the kinematic and dynamic studies of the marine robot and we have especially demonstrated by using the mathematical model under MATLAB in the last publication, that this ROV can move in a perfect environment without gravity or hydrodynamic dampers. In this article, we will study the behavior of this marine vehicle in a real environment with gravity and hydrodynamic dampers and we will view if this architectural solution can really allow the ROV to move and execute the given directional instructions.</span>
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Butcher, Paul A., Toby P. Piddocke, Andrew P. Colefax, Brent Hoade, Victor M. Peddemors, Lauren Borg, and Brian R. Cullis. "Beach safety: can drones provide a platform for sighting sharks?" Wildlife Research 46, no. 8 (2019): 701. http://dx.doi.org/10.1071/wr18119.
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Abstract ContextA series of unprovoked shark attacks on New South Wales (Australia) beaches between 2013 and 2015 triggered an investigation of new and emerging technologies for protecting bathers. Traditionally, bather protection has included several methods for shark capture, detection and/or deterrence but has often relied on environmentally damaging techniques. Heightened environmental awareness, including the important role of sharks in the marine ecosystem, demands new techniques for protection from shark attack. Recent advances in drone-related technologies have enabled the possibility of real-time shark detection and alerting. AimTo determine the reliability of drones to detect shark analogues in the water across a range of environmental conditions experienced on New South Wales beaches. MethodsA standard multirotor drone (DJI Inspire 1) was used to detect shark analogues as a proxy during flights at 0900, 1200 and 1500 hours over a 3-week period. The 27 flights encompassed a range of environmental conditions, including wind speed (2–30.0kmh−1), turbidity (0.4–6.4m), cloud cover (0–100%), glare (0–100%), seas (0.4–1.4m), swells (1.4–2.5m) and sea state (Beaufort Scale 1–5 Bf). Key resultsDetection rates of the shark analogues over the 27 flights were significantly higher for the independent observer conducting post-flight video analysis (50%) than for the drone pilot (38%) (Wald P=0.04). Water depth and turbidity significantly impaired detection of analogues (Wald P=0.04). Specifically, at a set depth of 2m below the water surface, very few analogues were seen by the observer or pilot when water turbidity reduced visibility to less than 1.5m. Similarly, when water visibility was greater than 1.5m, the detection rate was negatively related to water depth. Conclusions The present study demonstrates that drones can fly under most environmental conditions and would be a cost-effective bather protection tool for a range of user groups. ImplicationsThe most effective use of drones would occur during light winds and in shallow clear water. Although poor water visibility may restrict detection, sharks spend large amounts of time near the surface, therefore providing a practical tool for detection in most conditions.
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Kim, Yang-Hyun. "Duty Specification Training Plan for Utilizing Drone by the Marine Police." Korean Association of Maritime Police Science 9, no. 2 (May 31, 2019): 29–47. http://dx.doi.org/10.30887/jkmps.2019.9.2.029.
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Xin, Guipeng, Zhaoxi Cheng, and Jiexin Liu. "Design of Location Algorithm for Marine Drone Aircraft Maintenance Base Station." IOP Conference Series: Materials Science and Engineering 563 (August 9, 2019): 052030. http://dx.doi.org/10.1088/1757-899x/563/5/052030.
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Olmedo-Masat, O. Magalí, M. Paula Raffo, Daniel Rodríguez-Pérez, Marianela Arijón, and Noela Sánchez-Carnero. "How Far Can We Classify Macroalgae Remotely? An Example Using a New Spectral Library of Species from the South West Atlantic (Argentine Patagonia)." Remote Sensing 12, no. 23 (November 26, 2020): 3870. http://dx.doi.org/10.3390/rs12233870.
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Macroalgae have attracted the interest of remote sensing as targets to study coastal marine ecosystems because of their key ecological role. The goal of this paper is to analyze a new spectral library, including 28 macroalgae from the South-West Atlantic coast, in order to assess its use in hyperspectral remote sensing. The library includes species collected in the Atlantic Patagonian coast (Argentina) with representatives of brown, red, and green algae, being 22 of the species included in a spectral library for the first time. The spectra of these main groups are described, and the intraspecific variability is also assessed, considering kelp differentiated tissues and depth range, discussing them from the point of view of their effects on spectral features. A classification and an independent component analysis using the spectral range and simulated bands of two state-of-the-art drone-borne hyperspectral sensors were performed. The results show spectral features and clusters identifying further algae taxonomic groups, showing the potential applications of this spectral library for drone-based mapping of this ecological and economical asset of our coastal marine ecosystems.
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Putra, Akbar Kurnia, Afrilia Faradilla, and Bernard Sipahutar. "Underwater Drone: Aset Militer, Perangkat Penelitian dan Kedaulatan." PROGRESIF: Jurnal Hukum 16, no. 2 (February 7, 2022): 154–67. http://dx.doi.org/10.33019/progresif.v16i2.2509.
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This article discusses the legal issue of using underwater drones according to international maritime law and Indonesian national law. This discussion is necessary considering the use of underwater drones that cross national borders, there is no specific regulation. Therefore, it is necessary to make special arrangements regarding the use of underwater missiles both in terms of attack, spying, and marine data collection so that foreign countries do not freely operate underwater drones in the territorial sea of other countries and do not violate the right of peaceful passage as regulated. in UNCLOS 1982. The method used is normative legal research which examines the rules and regulations related to the issues discussed. The results of the study show that the government needs to strengthen the maritime security system in Indonesian territory and take firm action against persons involved in the entry of foreign military assets into Indonesian territory.
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Balsi, Marco, Monica Moroni, Valter Chiarabini, and Giovanni Tanda. "High-Resolution Aerial Detection of Marine Plastic Litter by Hyperspectral Sensing." Remote Sensing 13, no. 8 (April 16, 2021): 1557. http://dx.doi.org/10.3390/rs13081557.
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An automatic custom-made procedure is developed to identify macroplastic debris loads in coastal and marine environment, through hyperspectral imaging from unmanned aerial vehicles (UAVs). Results obtained during a remote-sensing field campaign carried out in the seashore of Sassari (Sardinia, Italy) are presented. A push-broom-sensor-based spectral device, carried onboard a DJI Matrice 600 drone, was employed for the acquisition of spectral data in the range 900−1700 nm. The hyperspectral platform was realized by assembling commercial devices, whereas algorithms for mosaicking, post-flight georeferencing, and orthorectification of the acquired images were developed in-house. Generation of the hyperspectral cube was based on mosaicking visible-spectrum images acquired synchronously with the hyperspectral lines, by performing correlation-based registration and applying the same translations, rotations, and scale changes to the hyperspectral data. Plastics detection was based on statistically relevant feature selection and Linear Discriminant Analysis, trained on a manually labeled sample. The results obtained from the inspection of either the beach site or the sea water facing the beach clearly show the successful separate identification of polyethylene (PE) and polyethylene terephthalate (PET) objects through the post-processing data treatment based on the developed classifier algorithm. As a further implementation of the procedure described, direct real-time processing, by an embedded computer carried onboard the drone, permitted the immediate plastics identification (and visual inspection in synchronized images) during the UAV survey, as documented by short video sequences provided in this research paper.
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Giordano, F., G. Mattei, C. Parente, F. Peluso, and R. Santamaria. "MICROVEGA (MICRO VESSEL FOR GEODETICS APPLICATION): A MARINE DRONE FOR THE ACQUISITION OF BATHYMETRIC DATA FOR GIS APPLICATIONS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-5/W5 (April 9, 2015): 123–30. http://dx.doi.org/10.5194/isprsarchives-xl-5-w5-123-2015.
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Bathymetric data are fundamental to produce navigational chart and sea-floor 3D models. They can be collected using different techniques and sensors on board of a variety of platforms, such as satellite, aircraft, ship and drone. The MicroVEGA drone is an Open Prototype of Autonomous Unmanned Surface Vessel (AUSV) conceived, designed and built to operate in the coastal areas (0-20 meters of depth), where a traditional boat is poorly manoeuvrable. It is equipped with a series of sensors to acquire the morpho-bathymetric high precision data. In this paper we presents the result of the first case study, a bathymetric survey carried out at Sorrento Marina Grande. This survey is a typical application case of this technology; the Open Prototype MicroVega has an interdisciplinary breath and it is going to be applied to various research fields. In future, it will expect to do new knowledge, new survey strategies and an industrial prototype in fiberglass.
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Giordano, Francesco, Gaia Mattei, Claudio Parente, Francesco Peluso, and Raffaele Santamaria. "Integrating Sensors into a Marine Drone for Bathymetric 3D Surveys in Shallow Waters." Sensors 16, no. 1 (December 29, 2015): 41. http://dx.doi.org/10.3390/s16010041.
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Lambertini, Alessandro, Massimiliano Menghini, Jacopo Cimini, Angelo Odetti, Gabriele Bruzzone, Marco Bibuli, Emanuele Mandanici, et al. "Underwater Drone Architecture for Marine Digital Twin: Lessons Learned from SUSHI DROP Project." Sensors 22, no. 3 (January 19, 2022): 744. http://dx.doi.org/10.3390/s22030744.
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The ability to observe the world has seen significant developments in the last few decades, alongside the techniques and methodologies to derive accurate digital replicas of observed environments. Underwater ecosystems present greater challenges and remain largely unexplored, but the need for reliable and up-to-date information motivated the birth of the Interreg Italy–Croatia SUSHI DROP Project (SUstainable fiSHeries wIth DROnes data Processing). The aim of the project is to map ecosystems for sustainable fishing and to achieve this goal a prototype of an Unmanned Underwater Vehicle (UUV), named Blucy, has been designed and developed. Blucy was deployed during project missions for surveying the benthic zone in deep waters of the Adriatic Sea with non-invasive techniques compared to the use of trawl nets. This article describes the strategies followed, the instruments applied and the challenges to be overcome to obtain an accurately georeferenced underwater survey with the goal of creating a marine digital twin.
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Suriyon, Tansuriyavong, Towa Kameda, Motoki Kyan, Hideto Koja, and Takashi Anezaki. "Development of Marine Robot to Collect Eggs of Coral Using Drone Flight Controller." IEEJ Transactions on Industry Applications 139, no. 2 (February 1, 2019): 193–98. http://dx.doi.org/10.1541/ieejias.139.193.
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Harasyn, Madison L., Wayne S. Chan, Emma L. Ausen, and David G. Barber. "Detection and tracking of belugas, kayaks and motorized boats in drone video using deep learning." Drone Systems and Applications 10, no. 1 (January 1, 2022): 77–96. http://dx.doi.org/10.1139/juvs-2021-0024.
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Aerial imagery surveys are commonly used in marine mammal research to determine population size, distribution and habitat use. Analysis of aerial photos involves hours of manually identifying individuals present in each image and converting raw counts into useable biological statistics. Our research proposes the use of deep learning algorithms to increase the efficiency of the marine mammal research workflow. To test the feasibility of this proposal, the existing YOLOv4 convolutional neural network model was trained to detect belugas, kayaks and motorized boats in oblique drone imagery, collected from a stationary tethered system. Automated computer-based object detection achieved the following precision and recall, respectively, for each class: beluga = 74%/72%; boat = 97%/99%; and kayak = 96%/96%. We then tested the performance of computer vision tracking of belugas and occupied watercraft in drone videos using the DeepSORT tracking algorithm, which achieved a multiple-object tracking accuracy (MOTA) ranging from 37% to 88% and multiple object tracking precision (MOTP) between 63% and 86%. Results from this research indicate that deep learning technology can detect and track features more consistently than human annotators, allowing for larger datasets to be processed within a fraction of the time while avoiding discrepancies introduced by labeling fatigue or multiple human annotators.
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Tasistro-Hart, Adrian, Adam Maloof, Blair Schoene, and Michael P. Eddy. "Astronomically forced hydrology of the Late Cretaceous sub-tropical Potosí Basin, Bolivia." GSA Bulletin 132, no. 9-10 (January 29, 2020): 1931–52. http://dx.doi.org/10.1130/b35189.1.
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Abstract Periodic variations in Earth’s orbital parameters force climate on local and global scales, with global responses particularly sensitive to the presence of ice sheets and their associated feedbacks. Therefore, determining whether orbital forcings influenced sedimentary records of the past, and if so, which had such an effect, can shed light on Earth’s climate sensitivity and global ice volume. To this end, we present a field- and drone-based cyclostratigraphy of the predominantly lacustrine El Molino Formation of the Late Cretaceous–Early Paleogene Potosí Basin in present day Bolivia, which contains carbonate mud parasequences that record fluctuating hydrological conditions, including ephemeral marine connections, from 73 Ma to 64 Ma. We introduce a novel methodology for incorporating drone imagery into a quantitative, three-dimensional stratigraphic model that generates an upward-younging quantity comparable to stratigraphic height, and we find that our model outperforms our own field measurements of stratigraphic height. We project drone imagery at two sites into the stratigraphic model to construct time series of outcrop color, which vary systematically with facies and track basin water depth. Spectral analysis of these time series reveals sedimentary periodicities corresponding to short eccentricity, precession, and semi-precession, which are corroborated with measurements of magnetic susceptibility from mudstones. We generate independent age models at both study areas from four new U-Pb chemical abrasion–isotope dilution–thermal ionization mass spectrometry (CA–ID–TIMS) ages, which are consistent with an orbital interpretation for observed sedimentary periodicities. Importantly, we observe the presence of obliquity-scale periodicity in sedimentation during a period of marine connection, suggesting that sea level oscillations were driven by obliquity. This observation is consistent with previous claims about the presence of a small, orbitally forced Antarctic ice sheet during the latest Cretaceous.
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E, Weimann,. "Citizen Research Highlights: Blue Flag Beach is not a Reliable Eco-Label to Protect Bathers in Cape Town." Journal of Environment and Ecology 9, no. 2 (November 25, 2018): 1. http://dx.doi.org/10.5296/jee.v9i2.13478.
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Background: Every day over 50 million liters of raw sewage are pumped into the Atlantic Ocean at several marine outfalls around the Cape Peninsula. They are in proximity to Blue Flag beaches and marine coastal nature reserves. This wastewater disposal poses severe health risks to citizens and recreational bathers. Moreover, sea food is contaminated by germs, pharmaceuticals, chemicals and other toxic substances. Caused by the wastewater pollution the marine ecosystem is under threat and deteriorating. Furthermore, Cape Town experiences recurrent droughts and the wastewater disposal puts additional strain to fresh water resources.Study design: The Blue Flag beach criteria were applied as a framework. A citizen research approach was used. Seawater was analysed daily over two months during high tide at Blue Flag beaches in Cape Town during Blue Flag season. Wind directions were recorded, photo documentation performed, and drone flights were conducted. Wastewater related diseases were reported by an online questionnaire.Results: The water at Blue Flag beaches in Cape Town is contaminated by E. coli. The drone flights showed that the sewage plume is shifted by wind directions, tides and currents towards the coast and Blue Flag beaches. Skin rashes, ear infections, stomach cramps, diarrhea as well as vomiting were reported by recreational bathers.Conclusions: The dissemination of sewage and other pollutants are influenced by wind directions and currents. The present sewage disposal into the sea poses a risk to the health of recreational bathers and sea food consumers. The International Blue Flag beach label promotes beaches as major tourist attractions but is not a reliable label indicating the cleanliness of water. Tertiary wastewater treatment plants are mandatory for coastal cities to protect the marine environment and recreational bathers. The appropriate recycling of wastewater is required to combat recurrent droughts to mitigate the climate crisis.
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Barbour, Terry E., Kenneth E. Sassaman, Angelica Maria Almeyda Zambrano, Eben North Broadbent, Ben Wilkinson, and Richard Kanaski. "Rare pre-Columbian settlement on the Florida Gulf Coast revealed through high-resolution drone LiDAR." Proceedings of the National Academy of Sciences 116, no. 47 (November 4, 2019): 23493–98. http://dx.doi.org/10.1073/pnas.1911285116.
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Drone-mounted, high-resolution light detection and ranging reveals the architectural details of an ancient settlement on the Gulf Coast of Florida without parallel in the Southeastern United States. The Raleigh Island shell-ring complex (8LV293) of ca. 900 to 1200 CE consists of at least 37 residential spaces enclosed by ridges of oyster shell up to 4 m tall. Test excavations in 10 of these residential spaces yielded abundant evidence for the production of beads from the shells of marine gastropods. Beads and other objects made from gulf coastal shell were integral to the political economies of second-millennium CE chiefdoms across eastern North America. At places as distant from the coast as the lower Midwest, marine gastropods were imported in raw form and converted into beads and other objects by craftspeople at the behest of chiefs. Bead making at Raleigh Island is exceptional not only for its level of production at the supply end of regional demand but also for being outside the purview of chiefly control. Here we introduce the newly discovered above-ground architecture of Raleigh Island and outline its analytical value for investigating the organization of shell bead production in the context of ancient political economies. The details of shell-ring architecture achieved with drone-mounted LiDAR make it possible to compare the bead making of persons distributed across residential spaces with unprecedented resolution.
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Chand, Subhash, and Barbara Bollard. "Detecting the Spatial Variability of Seagrass Meadows and Their Consequences on Associated Macrofauna Benthic Activity Using Novel Drone Technology." Remote Sensing 14, no. 1 (December 30, 2021): 160. http://dx.doi.org/10.3390/rs14010160.
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Seagrass meadows are undergoing significant decline locally and globally from human and climatic impacts. Seagrass decline also impacts seagrass-dependent macrofauna benthic activity, interrupts their vital linkage with adjacent habitats, and creates broader degradation through the ecosystem. Seagrass variability (gain and loss) is a driver of marine species diversity. Still, our understanding of macrofauna benthic activity distribution and their response to seagrass variability from remotely sensed drone imagery is limited. Hence, it is critical to develop fine-scale seasonal change detection techniques appropriate to the scale of variability that will apply to dynamic marine environments. Therefore, this research tested the performance of the VIS and VIS+NIR sensors from proximal low altitude remotely piloted aircraft system (RPAS) to detect fine-scale seasonal seagrass variability using spectral indices and a supervised machine learning classification technique. Furthermore, this research also attempted to identify and quantify macrofauna benthic activity from their feeding burrows and their response to seagrass variability. The results from VIS (visible spectrum) and VIS+NIR (visible and near-infrared spectrum) sensors produced a 90–98% classification accuracy. This accuracy established that the spectral indices were fundamental in this study to identify and classify seagrass density. The other important finding revealed that seagrass-associated macrofauna benthic activity showed increased or decreased abundance and distribution with seasonal seagrass variability from drone high spatial resolution orthomosaics. These results are important for seagrass conservation because managers can quickly detect fine-scale seasonal changes and take mitigation actions before the decline of this keystone species affects the entire ecosystem. Moreover, proximal low-altitude, remotely sensed time-series seasonal data provided valuable contributions for documenting spatial ecological seasonal change in this dynamic marine environment.
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Murakami, Ryota, Takumi Toyoshima, Daichi Furusawa, Masaru Suzuki, Kazunari Masumoto, Sho Owada, Yuichi Tsumaki, and Kyoichi Mori. "Logger Attaching System for Sperm Whales Using a Drone." Journal of Robotics and Mechatronics 33, no. 3 (June 20, 2021): 475–83. http://dx.doi.org/10.20965/jrm.2021.p0475.
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The biologging approach of attaching a logger to the body of an animal provides information that cannot be obtained by conventional direct visual observation. Marine zoologists have used this technique for observing sperm whales preying on giant squids in the deep sea. However, it is almost impossible to capture a sperm whale to attach a logger, because of its large size. Therefore, researchers have used a long pole to attach a logger from a ship to the back of sperm whales. Unfortunately, this method is risky and requires a skilled team. In this paper, we propose a logger attaching system using a drone to solve this problem. The proposed method can be trained on land; thus, it is relatively easy to train a team, and the mobility of the drone can shorten the installation time. Several pieces of equipment developed for the proposed method are described in detail. Furthermore, field experiments were performed with sperm whales to confirm the feasibility of the system. A suction cup of the seventh prototype of the whale rover was adsorbed onto the back of a sperm whale. Although a complete installation was not possible, it was demonstrated that operation was possible in a short time using the proposed method.
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Mury, Antoine, Antoine Collin, Thomas Houet, Emilien Alvarez-Vanhard, and Dorothée James. "Using Multispectral Drone Imagery for Spatially Explicit Modeling of Wave Attenuation through a Salt Marsh Meadow." Drones 4, no. 2 (June 24, 2020): 25. http://dx.doi.org/10.3390/drones4020025.
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Offering remarkable biodiversity, coastal salt marshes also provide a wide variety of ecosystem services: cultural services (leisure, tourist amenities), supply services (crop production, pastoralism) and regulation services including carbon sequestration and natural protection against coastal erosion and inundation. The consideration of this coastal protection ecosystem service takes part in a renewed vision of coastal risk management and especially marine flooding, with an emerging focus on “nature-based solutions.” Through this work, using remote-sensing methods, we propose a novel drone-based spatial modeling methodology of the salt marsh hydrodynamic attenuation at very high spatial resolution (VHSR). This indirect modeling is based on in situ measurements of significant wave heights (Hm0) that constitute the ground truth, as well as spectral and topographical predictors from VHSR multispectral drone imagery. By using simple and multiple linear regressions, we identify the contribution of predictors, taken individually, and jointly. The best individual drone-based predictor is the green waveband. Dealing with the addition of individual predictors to the red-green-blue (RGB) model, the highest gain is observed with the red edge waveband, followed by the near-infrared, then the digital surface model. The best full combination is the RGB enhanced by the red edge and the normalized difference vegetation index (coefficient of determination (R2): 0.85, root mean square error (RMSE): 0.20%/m).
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Mury, Antoine, Antoine Collin, and Dorothée James. "Morpho–Sedimentary Monitoring in a Coastal Area, from 1D to 2.5D, Using Airborne Drone Imagery." Drones 3, no. 3 (August 14, 2019): 62. http://dx.doi.org/10.3390/drones3030062.
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Coastal areas are among the most endangered places in the world, due to their exposure to both marine and terrestrial hazards. Coastal areas host more than two-thirds of the world’s population, and will become increasingly affected by global changes, in particular, rising sea levels. Monitoring and protecting the coastlines have impelled scientists to develop adequate tools and methods to spatially monitor morpho-sedimentary coastal areas. This paper presents the capabilities of the aerial drone, as an “all-in-one” technology, to drive accurate morpho-sedimentary investigations in 1D, 2D and 2.5D at very high resolution. Our results show that drone-related fine-resolution, high accuracies and point density outperform the state-of-the-science manned airborne passive and active methods for shoreline position tracking, digital elevation model as well as point cloud creation. We further discuss the reduced costs per acquisition campaign, the increased spatial and temporal resolution, and demonstrate the potentialities to carry out diachronic and volumetric analyses, bringing new perspectives for coastal scientists and managers.
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Hensel, Enie, Stephanie Wenclawski, and Craig Layman. "Using a small, consumer grade drone to identify and count marine megafauna in shallow habitats." Latin American Journal of Aquatic Research 46, no. 5 (November 10, 2018): 1025–33. http://dx.doi.org/10.3856/vol46-issue5-fulltext-15.
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Odzer, Michael N., Annabelle M. L. Brooks, Michael R. Heithaus, and Elizabeth R. Whitman. "Effects of environmental factors on the detection of subsurface green turtles in aerial drone surveys." Wildlife Research 49, no. 1 (February 4, 2022): 79–88. http://dx.doi.org/10.1071/wr20207.
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Abstract Context Aerial video surveys from unpiloted aerial systems (UAS) have become popular in wildlife research because of increased accessibility to remote areas, reduction of anthropogenic disruption to habitats and wildlife, low operating costs, and improved researcher safety. In shallow marine systems, they can provide opportunities to rapidly survey species that cannot easily be surveyed using boat- or land-based techniques. However, detectability of subsurface animals in marine habitats may be affected by environmental factors. Aims We investigated the effects of water depth, seagrass cover, surface glare, and observer numbers and expertise on the probability of detecting subsurface green turtles in UAS video surveys. Methods We deployed inanimate green turtle decoys at randomised intervals along 24 pre-determined transects across a depth gradient in a seagrass-dominated bay off Great Abaco, The Bahamas. We collected aerial videos of the transects by flying a DJI Phantom 3 Advanced quadcopter drone at an altitude of 10 m over each transect. Three independent observers watched each video and recorded decoy sightings to compare detection probabilities across observer experience levels. We used a generalised linear model to test for the effects of glare, water depth, wind speed, and seagrass cover on the detectability of turtle decoys. We also recorded glare conditions with aerial videos taken at 2-h intervals over a still body of water on cloudless days off North Miami, FL. Key results Individual observers performed similarly, but adding one additional observer increased detection by 11–12% and adding a third observer increased detections by up to 15%. Depth, seagrass cover, and glare significantly affected decoy detections. In both summer and fall, the optimal times and directions to minimise glare in aerial video surveys were 0800 hours, facing any direction other than north, and 1800 hours, facing any direction other than south. Conclusions The number of human observers and environmental variables, especially depth, seagrass cover, and glare, are important to explicitly consider when designing and analysing data from UAS surveys of subsurface animal abundances and distribution. Implications Our study draws attention to potential limitations of UAS-acquired data for subsurface observations if environmental conditions are not explicitly accounted for. Quantifying the effects of environmental factors, designing surveys to minimise variance in these factors, and having multiple observers are crucial for optimising UAS use in research and conservation of sea turtles and other marine fauna.
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Nababan, Bisman, La Ode Khairum Mastu, Nurul Hazrina Idris, and James P. Panjaitan. "Shallow-Water Benthic Habitat Mapping Using Drone with Object Based Image Analyses." Remote Sensing 13, no. 21 (November 5, 2021): 4452. http://dx.doi.org/10.3390/rs13214452.
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Spatial information on benthic habitats in Wangiwangi island waters, Wakatobi District, Indonesia was very limited in recent years. However, this area is one of the marine tourism destinations and one of the Indonesia’s triangle coral reef regions with a very complex coral reef ecosystem. The drone technology that has rapidly developed in this decade, can be used to map benthic habitats in this area. This study aimed to map shallow-water benthic habitats using drone technology in the region of Wangiwangi island waters, Wakatobi District, Indonesia. The field data were collected using a 50 × 50 cm squared transect of 434 observation points in March–April 2017. The DJI Phantom 3 Pro drone with a spatial resolution of 5.2 × 5.2 cm was used to acquire aerial photographs. Image classifications were processed using object-based image analysis (OBIA) method with contextual editing classification at level 1 (reef level) with 200 segmentation scale and several segmentation scales at level 2 (benthic habitat). For level 2 classification, we found that the best algorithm to map benthic habitat was the support vector machine (SVM) algorithm with a segmentation scale of 50. Based on field observations, we produced 12 and 9 benthic habitat classes. Using the OBIA method with a segmentation value of 50 and the SVM algorithm, we obtained the overall accuracy of 77.4% and 81.1% for 12 and 9 object classes, respectively. This result improved overall accuracy up to 17% in mapping benthic habitats using Sentinel-2 satellite data within the similar region, similar classes, and similar method of classification analyses.
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Frizziero, Leonardo, Alfredo Liverani, Giampiero Donnici, Enrico Conti, Beatrice Dello Preite, Umberto Lamanna, Christian Leon-Cardenas, and Matteo Garulli. "GD (Generative Design) Applied to a Plastics Recovery Drone (PRD) Using IDeS (Industrial Design Structure)." Inventions 6, no. 4 (November 5, 2021): 82. http://dx.doi.org/10.3390/inventions6040082.
Full textAbstract:
The evolution of innovative and systematic design methodologies over time has widened the design concept involvement from the product development phase, which also includes the production and start-up phases. Literature findings have presented to accomplish a Generative Design (GD) approach through the application of an innovative method called Industrial Structure Design (IDeS), a systematic design method able to discover the customer’s needs and the fundamental technical solutions to obtain a good innovative product, involving the whole organization for this achievement. Nevertheless, there is a social demand for solutions to the dramatic and growing problem of marine pollution from plastic materials, encouraging the designers to conceive a new innovative drone for waste collection at sea. Therefore, this study aims to merge all the most advanced design technologies with IDeS in an integrated way, by generating a structure that can also be adopted to plan the organization of a production company. The approach is validated with the design of the Recovery Plastic Drone (RPD) obtained with the IDeS methodology, combining Design and Product development phases, leading to a better and innovative solution for the market.
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Liao, Yu-Hsien, and Jih-Gau Juang. "Real-Time UAV Trash Monitoring System." Applied Sciences 12, no. 4 (February 10, 2022): 1838. http://dx.doi.org/10.3390/app12041838.
Full textAbstract:
This study proposes a marine trash detection system based on unmanned aerial vehicles (UAVs) and aims to replace manpower with UAVs to detect marine trash efficiently and provide information to government agencies regarding real-time trash pollution. Internet technology and computer–machine interaction were applied in this study, which involves the deployment of a marine trash detection system on a drone’s onboard computer for real-time calculations. Images of marine trash were provided to train a modified YOLO model (You Look Only Once networks). The UAV was shown to be able to fly along a predefined path and detect trash in coastal areas. The detection results were sent to a data streaming platform for data processing and analysis. The Kafka message queuing system and the Mongo database were used for data transmission and analysis. It was shown that a real-time drone map monitoring station can be built up at any place where mobile communication is accessible. While a UAV is automatically controlled by an onboard computer, it can also be controlled through a remote station. It was shown that the proposed system can perform data analysis and transmit heatmaps of coastal trash information to a remote site. From the heatmaps, government agencies can use trash categories and locations to take further action.