UAV-SfM and Geographic Object-Based Image Analysis for Measuring Multi-Temporal Planimetric and Volumetric Erosion of Arctic Coasts

Abstract

Monitoring and quantifying the rapid changes along Arctic coasts is becoming increasingly important as above average warming in the Arctic is contributing to increasing rates of erosion leading to dramatic impacts on coastal ecosystems and communities. Understanding the impacts of Arctic coastal erosion on the climate system across large coastal scales requires improvements in measurement techniques. We analyzed two coastal sites in Kugmallit Bay (near Tuktoyaktuk, Northwest Territories, Canada), over a one-week and one-year time interval. Using high-resolution imagery from Unoccupied Aerial Vehicles with Structure from Motion (UAV-SfM), we investigated the influence of unique coastal indicator features on reported planimetric and volumetric measurements and explored the use of Geographic Object Based Image Analysis (GEOBIA) to semi-automate the process of coastal feature extraction. We observed temporally dependent differences between coastal feature movements, planimetrically and volumetrically, and object-based feature extraction accuracy was found to be feature dependent. Our research has made methodological improvements to Arctic coastal measurements, particularly at high spatiotemporal scales, which highlights considerations relevant to broad scale Arctic coastal monitoring and quantification.

RÉSUMÉ

La surveillance et la quantification des changements rapides le long des côtes arctiques deviennent de plus en plus importantes, car un réchauffement supérieur à la moyenne dans l’Arctique contribue à l’augmentation des taux d’érosion, ce qui entraîne des répercussions dramatiques sur les écosystèmes et les communautés côtières. Pour comprendre les répercussions de l’érosion côtière en Arctique sur le système climatique à grande échelle, il faut améliorer les techniques de mesure. Nous avons analysé deux sites côtiers dans la baie de Kugmallit (près de Tuktoyaktuk, dans les Territoires du Nord-Ouest, au Canada), sur une période d’une semaine et d’un an. À l’aide d’images haute résolution de drones (UAV-SfM), nous avons étudié l’influence des caractéristiques particulières des côtes sur les mesures planimétriques et volumétriques rapportées et exploré l’utilisation de l’analyse d’images basée sur des objets géographiques (GEOBIA) pour semi-automatiser le processus d’extraction des rives. Nous avons observé des différences temporelles entre les changements des propriétés du rivage, planimétriques et volumétriques, et la précision de l’extraction des caractéristiques basée sur les objets s’est avérée dépendante de la nature des côtes. Notre recherche a apporté des améliorations méthodologiques pour la mesure des rivages de l’Arctique, en particulier à des échelles spatio-temporelles élevées, ce qui met en évidence des considérations pertinentes pour la surveillance et la quantification de l’érosion des côtes de l’Arctique à grande échelle.

Acknowledgments

We are grateful to the field crews, community members, and NRCan staff who worked on this project during the 2018 and 2019 field surveys, in particular, Angus Robertson, Paul Fraser, and Bay Berry for their contributions to the field logistics, and data collection. We would also like to acknowledge the community of Tuktoyaktuk, the Tuktoyaktuk Community Corporation, and the Tuktoyaktuk Hunters and Trappers Committee for their continued support. Permitting for this project fell under the NWT Science Licences: 16073 and 16286. Inuvialuit land administration land use permit ILA18TN005 and Parks Canada Research and Collection Permit PCL-2018-2761-02.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was funded by the Climate Change Geoscience Program (Natural Resources Canada), Crown-Indigenous Relations and Northern Affairs Canada (CIRNAC): (1) Climate Change preparedness in the North (CCPN); (2) Beaufort Sea Regional Strategic Environmental Assessment (BRSEA). As well, it was funded by a Natural Science and Engineering Council of Canada Discover grant and Northern supplement to BJM and by a Northern Student Training Program from Polar Knowledge Canada to AC.