ABSTRACT
Clark, A.; Moorman, B.; Whalen, D., and Vieira, G., 2025. Segmentation and classification of Pléiades Satellite imagery for complex shoreline proxy delineation in the Western Canadian Arctic.
Permafrost coasts are vulnerable to the effects of climate change, including above average warming in the Arctic, sea-level rise, and changes to sea-ice extent and duration. As a result, coastal erosion represents a prominent hazard that impacts communities and habitats locally, but it also potentially releases significant amounts of organic carbon that are consequential to understanding global greenhouse gas emissions, which requires appropriate quantification and monitoring. The extent and complexity of Arctic coasts represent a challenge for effective broad-scale monitoring using traditional methods of manual coastline delineation. In this study, an alternative to manual coastline delineation is presented using object-based image analysis to classify very high resolution Pléiades satellite imagery (0.5 m/pixel) scenes and subsequently extract two common coastline proxies, the tundra line and waterline.This study focused on three large, varied, coastal stretches in the Western Canadian Arctic: the Yukon North Slope, Tuktoyaktuk Peninsula, and Darnley Bay coasts. Twenty-five (25) images were classified with high accuracy (92% average), while the majority of extracted coastline proxies were within 3.0 m of the reference features and in many scenarios had accuracies better than 1.5 m, which is comparable to expected digitizing error, or loss of accuracy, associated with the variance of repeated shoreline digitization of the same coastal extent. This work presents an important step towards broad-scale Arctic coastal change monitoring and quantification through semi-automated classification and feature extraction techniques, which will also enhance contextual information useful in conducting richer Arctic coastal erosion studies.
