USAP-DC

New methodologies for the deployment of coordinated unmanned aerial vehicles will be developed with the aim of attaining whole-colony imagery that can be used to characterize nesting habitats of Adelie penguins at Cape Crozier, on Ross Island, Antarctica. This information will be used to test hypotheses regarding relationships between terrain characteristics, nesting density, and breeding success. This population, potentially the largest in the world and at the southern limit of the species' range, has doubled in size over the past 20 years while most other colonies in the region have remained stable or declined. New information gained from this project will be useful in understanding the potential of climate-driven changes in terrestrial nesting habitats for impacting Adelie penguins in the future. The project will produce, and document, open-source software tools to help automate image processing for automated counting of Adelie penguins. The project will train graduate and undergraduate students and contribute materials to ongoing educational outreach programs based on related penguin science projects. Information gained from this project will contribute towards building robust, cost-effective protocols for monitoring Adelie penguin populations, a key ecosystem indicator identified in the draft Ross Sea Marine Protected Area Research and Monitoring Plan. Adelie penguins are important indicators of ecosystem function and change in the Southern Ocean. In addition to facing rapid changes in sea ice and other factors in their pelagic environment, their terrestrial nesting habitat is also changing. Understanding the species' response to such changes is critical for assessing its ability to adapt to the changing climate. The objective of this project is to test several hypotheses about the influence of fine-scale nesting habitat, nest density, and breeding success of Adelie penguins in the Ross Sea region. To accomplish this, the project will develop algorithms to improve efficiency and safety of surveys by unmanned aerial systems and develop and disseminate an automated image processing workflow. Images collected during several UAV surveys will be used to estimate the number of nesting adults and chicks produced, as well as estimate nesting density in different parts of two colonies on Ross Island, Antarctica, that differ in size by two orders of magnitude. Imagery will be used to generate high resolution digital surface/elevation models that will allow terrain variables like flood risk and terrain complexity to be derived. Combining the surface model with the nest and chick counts at the two colonies will provide relationships between habitat covariates, nest density, and breeding success. The approaches developed will enable Adelie penguin population sizes and potentially several other indicators in the Ross Sea Marine Protected Area Research and Monitoring Plan to be determined and evaluated. The flight control algorithms developed have the potential to be used for many types of surveys, especially when large areas need to be covered in a short period with extreme weather potential and difficult landing options. Aerial images and video will be used to create useable materials to be included in outreach and educational programs. The automated image processing workflow and classification models will be developed as open source software and will be made freely available for others addressing similar wildlife monitoring challenges.

Person	Role
Ballard, Grant	Investigator and contact
Schmidt, Annie	Co-Investigator
Schwager, Mac	Co-Investigator
McKown, Matthew	Co-Investigator

Antarctic Organisms and Ecosystems

Award # 1834986

USAP-1834986_1

Deployment	Type
Grant Ballard	field camp

None in the Database

Repository	Title (link)	Format(s)	Status
USAP-DC	Orthomosaics of Ross Island Penguin Colonies 2019 - 2021	GeoTIFF	exists

1. Shah, K., Ballard, G., Schmidt, A., & Schwager, M. (2020). Multidrone aerial surveys of penguin colonies in Antarctica. Science Robotics, 5(47), eabc3000. (doi:10.1126/scirobotics.abc3000)
2. Shah, K., Schmidt, A. E., Ballard, G., & Schwager, M. (2022). Large scale aerial multi-robot coverage path planning. Field Robotics, 2, 1971–1998. (doi:10.55417/fr.2022064)
3. Clark, J., Shah, K., & Schwager, M. (2024). Online Path Repair: Adapting to Robot Failures in Multi-Robot Aerial Surveys. IEEE Robotics and Automation Letters, 9(3), 2319–2326. (doi:10.1109/lra.2024.3355730)