EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Probabilistic detection and tracking of icebergs in the Amundsen Sea embayment

Ben Evans1, Scott Hosking2, Andrew Fleming1, and Alan Lowe2
Ben Evans et al.
  • 1British Antarctic Survey, United Kingdom of Great Britain – England, Scotland, Wales (
  • 2Alan Turing Institute, United Kingdom of Great Britain – England, Scotland, Wales

Accurate estimates of iceberg populations, disintegration rates and iceberg movements are essential to understand ice sheet contributions to global sea level change and freshwater and heat balances. Knowledge and prediction of iceberg distributions is also important for the safety and efficiency of shipping operations in polar seas. The dynamics, persistence, fragmentation rates, melt rates and dispersal of icebergs are, however, poorly understood due to a lack of automated approaches for monitoring them. Better monitoring of icebergs would help parameterise the locations and quantities of freshwater and nutrient inputs within hydrographic and ecological models respectively and help mitigate collision hazards for navigation.

Here we present a combination of Bayesian approaches to the identification of icebergs in synthetic aperture radar imagery and their subsequent tracking across multiple years. For detection we use a Dirichlet Process Mixture Model, while for tracking we adapt Bayesian Tracker, a probabilistic multi-object tracking algorithm originally developed for cell microscopy applications. We are able to reconstruct iceberg paths and lineages, which we validate against synthetic data and manual annotations. We demonstrate that icebergs across the size distribution can be tracked successfully from their point of calving in dense fields of objects, through dispersal and fragmentation, to distal locations.

How to cite: Evans, B., Hosking, S., Fleming, A., and Lowe, A.: Probabilistic detection and tracking of icebergs in the Amundsen Sea embayment, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-6495,, 2023.