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dc.contributor.advisorJoLynn, Carroll
dc.contributor.authorAniceto, Ana Sofia Albuquerque Lima
dc.date.accessioned2018-10-22T13:31:14Z
dc.date.available2018-10-22T13:31:14Z
dc.date.issued2018-06-19
dc.description.abstractNew tools and methods are needed to monitor marine resources so that industrial activities can be conducted without (or at least minimizing) adverse impacts on species of concern. UAVs can be used as a complementary or alternative tool to current methods for monitoring and research of marine mammals. This study highlights current knowledge gaps and the need for further empirical testing of these systems. The capabilities of a system must be well understood before field trials are carried out. Platforms and sensors have different qualities and limitations, and will perform differently depending on the type of monitoring needed. When conducting field tests, it is important to acknowledge the many factors that may bias image analyses. Factors external to the survey equipment (such as environmental features) may affect UAV data differently than visual observer-based aerial survey data (hereby manned-surveys). Changes in pixel size due to aircraft movement may affect the resolution in which an animal is present within an image and is therefore a measure that should be included in analyses of digital imagery. Certainty of detections is a measure of relevance for such analyses as it provides a better understanding of the effects of environmental and survey-related covariates on image analysts' capabilities to detect an animal. Multiple aircraft or single aircraft maneuvers are often conducted to validate observations and estimate animal availability. To increase the number of detections when using multiple aircraft, one must consider animal availability parameters that can bias estimates of abundance or density. Simulation studies considering survey features and animal behavior can be used to improve data acquisition using digital imagery (e.g., deployed by UAVs). Overall, this highlights the complexity of monitoring programs, and shows how technological progress is valuable not only for environmental scientists, but also for industry managers and regulators.en_US
dc.description.doctoraltypeph.d.en_US
dc.description.popularabstractHow can scientists use drones to study whales? Drones (also known as UAV -Unmanned Aerial Vehicles) have recently received much attention in academic, industrial, and regulatory environments. Whale research and monitoring is one of the fields that has boosted the application of these systems, since ship and manned aerial surveys are often expensive and time consuming. Whales travel between vast areas and therefore require effective mitigation and monitoring schemes that inform management and conservation decisions. For mitigation of offshore operations, drones are proving to be an efficient tool to minimize the potential impacts of these activities on marine resources. For marine mammals in particular, drones appear more cost-efficient and safer to operate than traditional survey methods, though their effectiveness is still under debate. This study includes three stages of assessment of the utility of drones for marine mammal surveys in arctic and sub-arctic regions. First, we need to understand the capabilities of different types of drones available in the market, as well as their sensors, in order to replace traditional manned airplanes and ships. Scientists must have an overview of the state of technology, define the research objectives beforehand, and only then choose the most effective system. For research and monitoring offshore, fixed-wing powered drones are the best option given their long operational range. In the Arctic, there are many unexplored areas and the conditions can be challenging to survey. Field deployments should be also be tested and evaluated. To investigate how fixed-wing drones perform in these conditions, we conducted 12 field trials during summer and winter in Tromsø (Northern Norway). The drones followed pre-designed tracks, and took consecutive photos throughout the entire duration of the flights. A total of 288 sightings were found, of which 50 where humpback whales, 63 were killer whales, 57 where harbor porpoises, and 118 were unidentified species. After the flights, an image analyst classified each photo for environmental conditions, animal presence, and presence/absence certainty. The research team found that darker images (low levels of brightness) have a positive effect on observer's certainty of detection, whether the whales were breaking the water surface or were present just below the water. Sea conditions were found to have a negative effect on observer certainty, which shows that drones can be affected by environmental conditions in a similar way as traditional aerial surveys. Finally, since the deployment of several drones can be used to estimate the probability of detecting a whale and increase detection, computer simulations can be used as an additional approach. We tested the deployment of multiple drones and how the time delay between them can be used to optimize whale detections. Simulated flights overlapped with data from humpback whales were used to estimate the relationship between the time gaps between drones and the whales' diving cycle. Flights deployed at 5 to 6 minute-intervals following the same track gave the most detections, which matched the whale's average time between surfacing periods. This highlights the need for scientists to investigate not only how the technology has an impact on how we gather data but also how what we are studying can affect the amount and quality of data that we collect.en_US
dc.description.sponsorshipResearch Centre for Arctic Petroleum Exploration (ARCEx) Akvaplan-nivaen_US
dc.identifier.isbn978-82-8236-306-8 (trykt) og 978-82-8236-307-5 (pdf)
dc.identifier.urihttps://hdl.handle.net/10037/14008
dc.language.isoengen_US
dc.publisherUiT Norges arktiske universiteten_US
dc.publisherUiT The Arctic University of Norwayen_US
dc.relation.haspart<p>Paper I: Verfuss, U.K., Aniceto, A.S., Biuw, M., Fielding, S., Gillespie, D., Harris, D. … Wyatt, R. (2018). Understanding the current state of autonomous technologies to improve/expand observation and detection of marine species. (Manuscript). Full text not available in Munin. <p> <p>Paper II: Aniceto, A.S., Biuw, M., Lindstrøm, U., Solbø, S.A., Broms, F. & Carroll, J. (2018). Monitoring marine mammals using unmanned aerial vehicles: quantifying detection certainty. Available at <a href=http://hdl.handle.net/10037/13494>http://hdl.handle.net/10037/13494.</a> <p> <p>Paper III: Aniceto, A.S., Biuw, M., Lindstrøm, U., Marques, T. & Carroll, J. Unmanned Aerial Vehicles in whale research: using multiple aircraft. (Manuscript). Full text not available in Munin. <p>en_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2018 The Author(s)
dc.subject.courseIDDOKTOR-004
dc.subjectVDP::Technology: 500::Marine technology: 580::Other marine technology: 589en_US
dc.subjectVDP::Teknologi: 500::Marin teknologi: 580::Annen marin teknologi: 589en_US
dc.titleUnmanned aerial vehicles for marine mammal surveys in arctic and sub-arctic regionsen_US
dc.typeDoctoral thesisen_US
dc.typeDoktorgradsavhandlingen_US


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