SAR-based estimation of the baltic sea ice motion

Karvonen, Juha; Similä, M.; Lehtiranta, Jonni

doi:10.1109/igarss.2007.4423378

Cited by 16 publications

(12 citation statements)

References 4 publications

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“…SAR is widely used based on its all season capability for sea ice monitoring and C‐band SAR has traditionally been used to monitor both sea ice extent, concentration, and drift speed [e.g., Walker et al ., ; Maillard et al ., ; Karvonen et al ., ]. Work by Dierking and Busche [], Eriksson et al [] and Lehtiranta et al .…”

Section: Introductionmentioning

confidence: 96%

“…Synthetic aperture radar (SAR) satellites offer the opportunity to monitor the Arctic Ocean on a daily basis as they are not hindered by cloud cover nor by lack of daylight. SAR is widely used based on its all season capability for sea ice monitoring and C-band SAR has traditionally been used to monitor both sea ice extent, concentration, and drift speed [e.g., Walker et al, 2006;Maillard et al, 2005;Karvonen et al, 2007]. Work by Dierking and Busche [2006], Eriksson et al [2010] and Lehtiranta et al [2015] has identified that other SAR frequencies can contribute important information for sea ice classification.…”

Section: Introductionmentioning

confidence: 99%

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Combined observations of Arctic sea ice with near‐coincident colocated X‐band, C‐band, and L‐band SAR satellite remote sensing and helicopter‐borne measurements

et al. 2017

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In this study, we compare colocated near‐coincident X‐, C‐, and L‐band fully polarimetry SAR satellite images with helicopter‐borne ice thickness measurements acquired during the Norwegian Young sea ICE 2015 (N‐ICE2015) expedition in the region of the Arctic Ocean north of Svalbard in April 2015. The air‐borne surveys provide near‐coincident snow plus ice thickness, surface roughness data, and photographs. This unique data set allows us to investigate how the different frequencies can complement one another for sea ice studies, but also to raise awareness of limitations. X‐band and L‐band satellite scenes were shown to be a useful complement to the standard SAR frequency for sea ice monitoring (C‐band) for lead ice and newly formed sea ice identification. This may be in part be due to the frequency but also the high spatial resolution of these sensors. We found a relatively low correlation between snow plus ice thickness and surface roughness. Therefore, in our dataset ice thickness cannot directly be observed by SAR which has important implications for operational ice charting based on automatic segmentation.

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Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Combined observations of Arctic sea ice with near‐coincident colocated X‐band, C‐band, and L‐band SAR satellite remote sensing and helicopter‐borne measurements

et al. 2017

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“…In a quest to automate this process, many image processing algorithms were adapted from other fields of research to improve the estimation. Some of these algorithms are briefly described in the following discussion, with the readers directed to other works on motion tracking for more details [18]- [20], [29], [30], [33], [36], [37], [53], [62], [63].…”

Section: Background Studiesmentioning

confidence: 99%

Motion Tracking of Discontinuous Sea Ice

Thomas

Kambhamettu

Geiger

2011

IEEE Trans. Geosci. Remote Sensing

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The purpose of this paper is twofold: 1) to develop a high-resolution sea ice motion tracking system at the geospatial mesoscale (1-100 km 2 ) and 2) to propose an algorithm that measures motion at close proximity to discontinuous regions. Here, we present a motion tracking system that computes differential motion at 400 m resolution and validate the accuracy/precision of this system via four studies. The first study measures the accuracy against displacements measured from in situ Global Positioning System (GPS) buoys deployed at the Sea-ice Experiment: Dynamic Nature of the Arctic (SEDNA) and the Surface HEat Budget of the Arctic Ocean (SHEBA) experiments. The estimates are found to be statistically comparable with GPS, with an average error of 361.9 and 600.6 m for the experiments, respectively. The second study compares the estimated displacements to those measured by the RADARSAT Geophysical Processing System. A precision error of 75.7 m is found between the two motion tracking systems. The third study uses intensity warping of randomly sampled measurements to evaluate discontinuous motion tracking. A one-tailed Wilcoxon signed rank test is used to validate these measurements at α = 0.01. Results from this paper prove that anisotropic smoothing produces significantly smaller errors at discontinuous locations (W = 4240 and p < 0.001) over conventional isotropic smoothing. The fourth study compares displacements measured by anisotropic smoothing against manual measurements. This paper demonstrates an average reduction of the estimation error by 50 m with the use of anisotropic smoothing over the conventional isotropic smoothing.

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“…Observations of the Baltic sea ice are for winter navigation safety. Work has been done to calculate sea ice motion from two consecutive satellite images using different optical flow estimation algorithms (e.g., Fily and Rothrock, 1987;Vesecky et al, 1988;Liu et al, 1997;Karvonen et al, 2007;Thomas et al, 2011), and this approach has provided acceptable results using the C-band synthetic aperture radar, which is regarded as a good compromise for sea ice remote sensing (Dierking and Busche, 2006). This work will compare C-band (38-75 mm wavelength) with L-band (150-300 mm wavelength) for sea ice motion estimation.…”

Section: Introductionmentioning

confidence: 99%

“…Finally, the high-resolution result was median-filtered to remove prob-140 lematic values. For this work, the median filtering radius was chosen to be 3 (as in Karvonen et al, 2007).…”

mentioning

confidence: 99%

Comparing C- and L-band SAR images for sea ice motion estimation

2015

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Abstract.Pairs of consecutive C-band synthetic-aperture radar (SAR) images are routinely used for sea ice motion estimation. The L-band radar has a fundamentally different character, as its longer wavelength penetrates deeper into sea ice. L-band SAR provides information on the seasonal sea ice inner structure in addition to the surface roughness that dominates C-band images. This is especially useful in the Baltic Sea, which lacks multiyear ice and icebergs, known to be confusing targets for L-band sea ice classification. In this work, L-band SAR images are investigated for sea ice motion estimation using the well-established maximal crosscorrelation (MCC) approach. This work provides the first comparison of L-band and C-band SAR images for the purpose of motion estimation. The cross-correlation calculations are hardware accelerated using new OpenCL-based source code, which is made available through the author's web site. It is found that L-band images are preferable for motion estimation over C-band images. It is also shown that motion estimation is possible between a C-band and an L-band image using the maximal cross-correlation technique.

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SAR-based estimation of the baltic sea ice motion

Cited by 16 publications

References 4 publications

Combined observations of Arctic sea ice with near‐coincident colocated X‐band, C‐band, and L‐band SAR satellite remote sensing and helicopter‐borne measurements

Combined observations of Arctic sea ice with near‐coincident colocated X‐band, C‐band, and L‐band SAR satellite remote sensing and helicopter‐borne measurements

Motion Tracking of Discontinuous Sea Ice

Comparing C- and L-band SAR images for sea ice motion estimation

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