The environmental changes caused by climate change and the actions taken by modern societies to mitigate and to adapt to these changes are currently leading to an increased utilization of marine resources with potential effects on marine life. Baseline information on the distribution and abundance of marine species is required in order to determine the state of the marine environment in a rapidly changing world, as well as to assess the conservation status of its inhabitants. This requires effective monitoring schemes that can provide meaningful data, and detailed vulnerability assessment maps to inform policy decisions. New 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. Marine mammals are particularly vulnerable because underwater noise interferes with animal behavior and physiology. This has encouraged research and development of the use of unmanned aerial vehicles (UAVs) as a new method of monitoring and detecting marine mammals. UAVs are a method of providing insights of marine mammal presence particularly in arctic and sub-arctic regions. The research conducted under this doctoral program accompanies and fills some of the knowledge gaps on the application of these systems, while highlighting the need for more detailed material on marine mammal populations, their distribution, and abundance. The three components described in this doctoral thesis involve three stages of assessment of the utility of UAV systems for marine mammal surveys in arctic and sub-arctic regions. Each of the components highlight current knowledge gaps and the need for further empirical testing of these systems. The selection of a platform and sensor depends on the research and monitoring goals. 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. It is therefore important to take these into account when planning deployments. 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. The permanent record of each survey provided by digital technology allows scientists to reduce the effect of observer bias. 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). The number of detections may be considered a time series and should be analyzed based on the frequency of occurrance, so that further analyses for correlation with whale diving cycles can be performed. The work presented here 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.
Aniceto, A.S. (2018): Unmanned aerial vehicle for marine mammal studies in arctic and sub-arcric regions. A dissertation for the degree of Philosophiae Doctor, June 2018. UiT The Arctic University of Norway. ISBN: 978-82-8236-307-5. Permanent link: http://hdl.handle.net/10037/14008. [intranet]