![]() In particular, although scatterometers facilitate daily position and motion observations of large icebergs with a coarse spatial resolution (Budge and Long, 2018 Stuart and Long, 2011a, b), SAR instruments have a more significant advantage in precise observations of iceberg area changes due to their relatively fine spatial resolution. ![]() In contrast, SAR images can be used for analysis regardless of the weatherĬonditions or time of year (Han et al., 2019 Mazur et al., 2017 Wesche and Dierking, 2012). Icebergs, they cannot be used during polar night or under cloudy conditions. While multispectral images can be useful for observing Radar remote sensing, including scatterometer and synthetic aperture radar (SAR), is an efficient tool for monitoring both movements and area changes of icebergs. Therefore, detecting and tracking icebergs is extremely important to understand the changing sea ice, ocean, and atmosphere in the polar regions. ![]() Icebergs can threaten ship navigation (Lasserre, 2015). (Martin et al., 2007 Merino et al., 2016), dissolved iron concentration (LinĮt al., 2011 De Jong et al., 2015), and ecosystems and biology (Wilson et al., 2016 Schwarz and Schodlok, 2009 Biddle et al., 2015). In addition, the formation and melting of icebergs influence global climate (Romanov et al., 2008 Mackie et al., 2020), ocean flux (SilvaĮt al., 2006 Rackow et al., 2017 Starr et al., 2021), sea ice production Provide important insights for the interaction of these variables (Schodlok et al., 2006). Since the trajectories and speeds of icebergs also depend on multiple and complexĮnvironmental variables (ocean, atmosphere, sea ice, etc.), icebergs Considering the majority of an iceberg is under water, iceberg drift is a good indicator of ocean circulation (Collares et al., 2018). An iceberg has a lifespan of several years or longer, and its area ranges from a few square kilometers to thousands of square kilometers. When a large ice mass breaks off from an ice shelf or glacier into the ocean, it forms an iceberg. The semi-automated iceberg tracking based on the storage capacity and computing power of GEE can be used for this purpose. ![]() Considering the complexity of modeling icebergs, there is a demand for a large iceberg database to better understand the behavior of icebergs and their interactions with surrounding environments. Predominantly driven by the westward-flowing Antarctic Coastal Current, which dominates the circulation of the region. Given that the bulk of the iceberg is under water ( ∼30–60 m freeboard and ∼150–400 m thickness), its motion is Since the iceberg is generally surrounded byĬompacted sea ice, its drift correlates in part with sea ice motion and wind velocity. Implies that these variables may be related to mechanisms causing the Of low sea ice concentration, warm air temperature, and high waves. Periods with sudden losses of area (i.e., split-offs) coincide with periods Using thisĪpproach, we successfully track iceberg B43 from the Amundsen Sea to the Ross Sea and examine its changes in area, speed, and direction. In subsequent days with the CDH of the reference target iceberg. Next, we automatically choose and trace the location of the target iceberg byĬomparing the centroid distance histograms (CDHs) of all detected icebergs First, to detect all candidate icebergs in Sentinel-1 images, we employ an object-based image segmentation (simple non-iterative clustering – SNIC) and a traditional backscatter threshold method. This study, we process Sentinel-1 data via GEE to detect and track the drift of iceberg B43 during its lifespan of 3 years (2017–2020) in the Southern Ocean. The Google Earth Engine (GEE) cloud-based platform allows processing of a large quantity of Sentinel-1 images, saving time and computational resources. Sentinel-1 C-band synthetic aperture radar (SAR) images can be used to observe the drift of icebergs over the Southern Ocean with around 1–3 d of temporal resolution and 10–40 m of spatial resolution.
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