Algorithm to Detect Deformed Sea Ice Area in Seasonal Ice Zones Using L-band SAR Images

Abstract:

In order to improve the understanding of the dynamical deformation processes of sea ice in the seasonal ice zone (SIZ), an algorithm to detect deformed ice area was developed and validated using satellite L-band synthetic aperture radar (ScanSAR) images for the southern Sea of Okhotsk, where deformation processes play a crucial role in the ice thickening process. To approach, sea ice was categorized into three ice types: nilas (thin level), pancake ice (thin rough), and deformed ice (thick rough), and then the algorithm to classify into these categories was developed using ALOS/PALSAR as a function of backscatter coefficients at HH polarization (σ_HH⁰) and incidence angle (θ_i), based on the field observations. Comparative analysis confirmed that PALSAR can detect deformed ice more efficiently than Radarsat-2 (C-band SAR). The temporal evolution of the area, judged as deformed ice from this algorithm, shows significant variability with both time and space, and deformed ice area appears in relatively linear alignments with a width of a few tens of kilometers in the inner ice pack region, consistent with ice drift convergence. To confirm the results, PALSAR-2 images at HH and HV polarizations were examined as a function of θ_i, based on the four-year field observations in the same area. The results revealed that σ_HH⁰ and σ_HV⁰ are both subject to floe sizes as well as deformed ice, and σ_HV⁰ is more sensitive. This is because scattering at the ice margin also affects the radar signal. This indicates that care should be taken when applying this algorithm to the ice areas where significantly small floes are dominant like the marginal ice zone. We plan to extend this result to the Arctic Ocean, using the field data and PALSAR-2 images collected during the international research expedition, “Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)”, which is ongoing in the Arctic Ocean from October 2019 to October 2020.