Observation of melt onset on multiyear Arctic sea ice using the ERS 1 synthetic aperture radar

1994 ◽  
Vol 99 (C11) ◽  
pp. 22425 ◽  
Author(s):  
D. P. Winebrenner ◽  
E. D. Nelson ◽  
R. Colony ◽  
R. D. West
Keyword(s):  
Sea Ice ◽  
Synthetic Aperture Radar ◽  
Arctic Sea Ice ◽  
Synthetic Aperture ◽  
Arctic Sea ◽  
Aperture Radar

scholarly journals A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery

Elem Sci Anth ◽  
2017 ◽  
Vol 5 ◽  
Author(s):  
Byongjun Hwang ◽  
Jinchang Ren ◽  
Samuel McCormack ◽  
Craig Berry ◽  
Ismail Ben Ayed ◽  
...  
Keyword(s):  
Sea Ice ◽  
Synthetic Aperture Radar ◽  
Size Distribution ◽  
Ground Truth ◽  
Arctic Sea Ice ◽  
Synthetic Aperture ◽  
Distribution Data ◽  
Synthetic Aperture Radar Data ◽  
Arctic Sea ◽  
Aperture Radar

In this study, we present an algorithm for summer sea ice conditions that semi-automatically produces the floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar data. Currently, floe size distribution data from satellite images are very rare in the literature, mainly due to the lack of a reliable algorithm to produce such data. Here, we developed the algorithm by combining various image analysis methods, including Kernel Graph Cuts, distance transformation and watershed transformation, and a rule-based boundary revalidation. The developed algorithm has been validated against the ground truth that was extracted manually with the aid of 1-m resolution visible satellite data. Comprehensive validation analysis has shown both perspectives and limitations. The algorithm tends to fail to detect small floes (mostly less than 100 m in mean caliper diameter) compared to ground truth, which is mainly due to limitations in water-ice segmentation. Some variability in the power law exponent of floe size distribution is observed due to the effects of control parameters in the process of de-noising, Kernel Graph Cuts segmentation, thresholds for boundary revalidation and image resolution. Nonetheless, the algorithm, for floes larger than 100 m, has shown a reasonable agreement with ground truth under various selections of these control parameters. Considering that the coverage and spatial resolution of satellite Synthetic Aperture Radar data have increased significantly in recent years, the developed algorithm opens a new possibility to produce large volumes of floe size distribution data, which is essential for improving our understanding and prediction of the Arctic sea ice cover.

scholarly journals Consistent ice and open water classification combining historical synthetic aperture radar satellite images from ERS-1/2, Envisat ASAR, RADARSAT-2 and Sentinel-1A/B

2020 ◽  
Vol 61 (82) ◽  
pp. 40-50 ◽  
Author(s):  
A. Malin Johansson ◽  
Eirik Malnes ◽  
Sebastian Gerland ◽  
Anca Cristea ◽  
Anthony P. Doulgeris ◽  
...  
Keyword(s):  
Sea Ice ◽  
Synthetic Aperture Radar ◽  
Satellite Images ◽  
Satellite Image ◽  
Open Water ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Synthetic Aperture ◽  
Envisat Asar ◽  
Aperture Radar

AbstractSynthetic Aperture Radar (SAR) satellite images are used to monitor Arctic sea ice, with systematic data records dating back to 1991. We propose a semi-supervised classification method that separates open water from sea ice and can utilise ERS-1/2, Envisat ASAR, RADARSAT-2 and Sentinel-1 SAR images. The classification combines automatic segmentation with a manual segment selection stage. The segmentation algorithm requires only the backscatter intensities and incidence angle values as input, therefore can be used to establish a consistent decadal sea ice record. In this study we investigate the sea ice conditions in two Svalbard fjords, Kongsfjorden and Rijpfjorden. Both fjords have a seasonal ice cover, though Rijpfjorden has a longer sea ice season. The satellite image dataset has weekly to daily records from 2002 until now, and less frequent records between 1991 and 2002. Time overlap between different sensors is investigated to ensure consistency in the reported sea ice cover. The classification results have been compared to high-resolution SAR data as well as in-situ measurements and sea ice maps from Ny-Ålesund. For both fjords the length of the sea ice season has shortened since 2002 and for Kongsfjorden the maximum sea ice coverage is significantly lower after 2006.

scholarly journals Waveform classification of airborne synthetic aperture radar altimeter over Arctic sea ice

2013 ◽  
Vol 7 (4) ◽  
pp. 1315-1324 ◽  
Author(s):  
M. Zygmuntowska ◽  
K. Khvorostovsky ◽  
V. Helm ◽  
S. Sandven
Keyword(s):  
Sea Ice ◽  
Synthetic Aperture Radar ◽  
Arctic Sea Ice ◽  
Synthetic Aperture ◽  
The Arctic ◽  
Ice Thickness ◽  
Radar Altimeter ◽  
Sea Ice Thickness ◽  
Ku Band ◽  
Aperture Radar

Abstract. Sea ice thickness is one of the most sensitive variables in the Arctic climate system. In order to quantify changes in sea ice thickness, CryoSat-2 was launched in 2010 carrying a Ku-band radar altimeter (SIRAL) designed to measure sea ice freeboard with a few centimeters accuracy. The instrument uses the synthetic aperture radar technique providing signals with a resolution of about 300 m along track. In this study, airborne Ku-band radar altimeter data over different sea ice types have been analyzed. A set of parameters has been defined to characterize the differences in strength and width of the returned power waveforms. With a Bayesian-based method, it is possible to classify about 80% of the waveforms from three parameters: maximum of the returned power waveform, the trailing edge width and pulse peakiness. Furthermore, the maximum of the power waveform can be used to reduce the number of false detections of leads, compared to the widely used pulse peakiness parameter. For the pulse peakiness the false classification rate is 12.6% while for the power maximum it is reduced to 6.5%. The ability to distinguish between different ice types and leads allows us to improve the freeboard retrieval and the conversion from freeboard into sea ice thickness, where surface type dependent values for the sea ice density and snow load can be used.

scholarly journals Comparison of Target Detectors to Identify Icebergs in Quad-Polarimetric L-Band Synthetic Aperture Radar Data

2021 ◽  
Vol 13 (9) ◽  
pp. 1753
Author(s):  
Johnson Bailey ◽  
Armando Marino ◽  
Vahid Akbari
Keyword(s):  
Sea Ice ◽  
Synthetic Aperture Radar ◽  
Roc Curves ◽  
Radar Data ◽  
Open Ocean ◽  
Synthetic Aperture ◽  
False Alarms ◽  
Synthetic Aperture Radar Data ◽  
Whitening Filter ◽  
Aperture Radar

Icebergs represent hazards to ships and maritime activities and therefore their detection is essential. Synthetic Aperture Radar (SAR) satellites are very useful for this, due to their capability to acquire data under cloud cover and during day and night passes. In this work, we compared six state-of-the-art polarimetric target detectors to test their performance and ability to detect small-sized icebergs <120 m in four locations in Greenland. We used four single-look complex (SLC) ALOS-2 quad-polarimetric images from JAXA for quad-polarimetric detection and we compared with dual-polarimetric detectors using only the channels HH and HV. We also compared these detectors with single-polarimetric intensity channels and we tested using two scenarios: open ocean and sea ice. Our results show that the multi-look polarimetric whitening filter (MPWF) and the optimal polarimetric detector (OPD) provide the most optimal performance in quad- and dual-polarimetric mode detection. The analysis shows that, overall, quad-polarimetric detectors provide the best detection performance. When the false alarm rate (PF) is fixed to 10-5, the probabilities of detection (PD) are 0.99 in open ocean and 0.90 in sea ice. Dual-polarimetric or single-polarimetric detectors show an overall reduction in performance (the ROC curves show a decrease), but this degradation is not very large (<0.1) when the value of false alarms is relatively high (i.e., we are interested in bigger icebergs with a brighter backscattering >120 m, as they are easier to detect). However, the differences between quad- and dual- or single-polarimetric detectors became much more evident when the PF value was fixed to low detection probabilities 10-6 (i.e., smaller icebergs). In the single-polarimetric mode, the HV channel showed PD values of 0.62 for open ocean and 0.26 for sea ice, compared to values of 0.81 (open ocean) and 0.77 (sea ice) obtained with quad-polarimetric detectors.

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