Iceberg Detection With RADARSAT-2 Quad-Polarimetric C-Band SAR in Kongsfjorden, Svalbard—Comparison With a Ground-Based Radar

Citation

Bailey J, Akbari V, Liu T, Lauknes TR & Marino A (2024) Iceberg Detection With RADARSAT-2 Quad-Polarimetric C-Band SAR in Kongsfjorden, Svalbard—Comparison With a Ground-Based Radar. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, pp. 5790-5803. https://doi.org/10.1109/jstars.2024.3369392

Abstract
Satellite monitoring of icebergs in the Arctic region is paramount for the safety of shipping and maritime activities. The potential of polarimetric synthetic aperture radar data in enhancing detection capabilities of icebergs under interchangeable and challenging conditions is explored in this work. We introduce RADARSAT-2 quad-pol C -band data to detect icebergs in Kongsfjorden, Svalbard. The location contains two tidewater glaciers and is chosen because multiple processes are present in this region, such as ice formation and its relationship with the glaciers, freshwater discharge. Six state-of-the-art detectors are tested for detection performance. These are the dual-intensity polarization ratio anomaly detector, polarimetric notch filter, polarimetric match filter, symmetry, polarimetric whitening filter (PWF), and optimal polarimetric detector (OPD). In addition, we also tested the parameters of the Cloude–Pottier decomposition. In this study, we make use of a ground-based radar for validation and comparison with satellite images. We show that in calm sea-state conditions, the OPD and PWF detectors give high probability of detection ( PD ) values of 0.7–0.8 when the probability of false alarm ( PF ) value is 0.01–0.05, compared with choppy sea conditions where the same detectors have degraded performance ( PD = 0.5–0.7). Target-to-clutter ratio (TCR) values for each polarization channel is also extracted and compared to the icebergs’ dimensions. The ground-based radar shows higher values in TCR, compared with satellite images. These findings corroborate previous work and show that sea-ice activity, surface roughness, incidence angle, weather, and sea-state conditions all affect the sensitivity of the detectors for this task.

Keywords
Atmospheric Science; Computers in Earth Sciences

Journal
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing: Volume 17

People

Dr Vahid Akbari

Lect in Artificial Intelligence/Data Sci, Computing Science and Mathematics - Division

Mr Sonny Bailey

PhD Researcher, Biological and Environmental Sciences

Dr Armando Marino

Associate Professor, Biological and Environmental Sciences