scholarly journals Sensitivity of Radar Altimeter Waveform to Changes in Sea Ice Type at Resolution of Synthetic Aperture Radar

2019 ◽  
Vol 11 (22) ◽  
pp. 2602 ◽  
Author(s):  
Wiebke Aldenhoff ◽  
Céline Heuzé ◽  
Leif E. B. Eriksson
Keyword(s):  
Sea Ice ◽  
Synthetic Aperture Radar ◽  
Synthetic Aperture ◽  
Altimeter Data ◽  
Small Scale ◽  
High Peak Power ◽  
Radar Altimeter ◽  
Basin Scale ◽  
Sar Imagery ◽  
Aperture Radar

Radar altimetry in the context of sea ice has mostly been exploited to retrieve basin-scale information about sea ice thickness. In this paper, we investigate the sensitivity of altimetric waveforms to small-scale changes (a few hundred meters to about 10 km) of the sea ice surface. Near-coincidental synthetic aperture radar (SAR) imagery and CryoSat-2 altimetric data in the Beaufort Sea are used to identify and study the spatial evolution of altimeter waveforms over these features. Open water and thin ice features are easily identified because of their high peak power waveforms. Thicker ice features such as ridges and multiyear ice floes of a few hundred meters cause a response in the waveform. However, these changes are not reflected in freeboard estimates. Retrieval of robust freeboard estimates requires homogeneous floes in the order of 10 km along-track and a few kilometers to both sides across-track. We conclude that the combination of SAR imagery and altimeter data could improve the local sea ice picture by extending spatially scarce freeboard estimates to regions of similar SAR signature.

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 BEPERS pilot study: an experiment with X-band synthetic aperture radar over Baltic Sea ice

1992 ◽  
Vol 38 (128) ◽  
pp. 23-35 ◽  
Author(s):  
Matti Leppäranta ◽  
Rlsto Kuittinen ◽  
Jan Askne
Keyword(s):  
Pilot Study ◽  
Sea Ice ◽  
Synthetic Aperture Radar ◽  
Baltic Sea ◽  
Open Water ◽  
Synthetic Aperture ◽  
Speckle Reduction ◽  
X Band ◽  
Sar Imagery ◽  
Aperture Radar

Abstract Remote-sensing methods are the primary ones used for ice mapping in the Baltic Sea. A major methodological improvement is now being introduced by satellite radars due to their weather independency and high resolution. To learn how to use ERS-1 synthetic aperture radar (SAR) data, an extensive field programme BEPERS (Bothnian Experiment in Preparation for ERS-1) with airborne SARs has been arranged. The BEPERS pilot study was undertaken in 1987 using the French VARAN-S X-band SAR. The SAR was flown on 1 day over four study areas of size approximately 10 km x 50 km, and intensive validation observations were made. The data were most useful for the education they provided on how to work with SAR in sea-ice mapping. They have been used for developing SAR image-analysis methods, back-scatter modelling investigations and geophysical validation of SAR imagery. Cleaning-up of images consisted of speckle reduction and segmentation. Back-scatter characteristics of undeformed ice and ridges were examined. Ice-type classification was based on the box-classification method. Eight ice types were defined but basically only two types, undeformed ice/open water and deformed ice, could be discriminated. Two basic problems of high practical importance remained: how to discriminate between (1) open water and undeformed ice, and (2) ridged ice and brash ice. The data further showed illustrative examples of SAR imagery over sea ice.

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

2013 ◽  
Vol 7 (2) ◽  
pp. 1215-1242
Author(s):  
M. Zygmuntowska ◽  
K. Khvorostovsky ◽  
V. Helm ◽  
S. Sandven
Keyword(s):  
Sea Ice ◽  
Synthetic Aperture Radar ◽  
Waveform Analysis ◽  
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 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 has been analyzed. A set of parameters has been defined to characterize the difference in strength and width of the returned power waveforms. With a Bayesian based method it is possible to classify about 80% of the waveforms by three parameters: maximum of the returned power echo, the trailing edge width and pulse peakiness. Furthermore, the radar power echo maximum can be used to minimize the rate of false detection of leads compared to the widely used Pulse Peakiness parameter. The possibility to distinguish between different ice types and open water allows to improve the freeboard retrieval and the conversion into sea ice thickness where surface type dependent values for the sea ice density and snow load can be used.

scholarly journals BEPERS pilot study: an experiment with X-band synthetic aperture radar over Baltic Sea ice

1992 ◽  
Vol 38 (128) ◽  
pp. 23-35
Author(s):  
Matti Leppäranta ◽  
Rlsto Kuittinen ◽  
Jan Askne
Keyword(s):  
Pilot Study ◽  
Sea Ice ◽  
Synthetic Aperture Radar ◽  
Baltic Sea ◽  
Open Water ◽  
Synthetic Aperture ◽  
Speckle Reduction ◽  
X Band ◽  
Sar Imagery ◽  
Aperture Radar

AbstractRemote-sensing methods are the primary ones used for ice mapping in the Baltic Sea. A major methodological improvement is now being introduced by satellite radars due to their weather independency and high resolution. To learn how to use ERS-1 synthetic aperture radar (SAR) data, an extensive field programme BEPERS (Bothnian Experiment in Preparation for ERS-1) with airborne SARs has been arranged. The BEPERS pilot study was undertaken in 1987 using the French VARAN-S X-band SAR. The SAR was flown on 1 day over four study areas of size approximately 10 km x 50 km, and intensive validation observations were made. The data were most useful for the education they provided on how to work with SAR in sea-ice mapping. They have been used for developing SAR image-analysis methods, back-scatter modelling investigations and geophysical validation of SAR imagery. Cleaning-up of images consisted of speckle reduction and segmentation. Back-scatter characteristics of undeformed ice and ridges were examined. Ice-type classification was based on the box-classification method. Eight ice types were defined but basically only two types, undeformed ice/open water and deformed ice, could be discriminated. Two basic problems of high practical importance remained: how to discriminate between (1) open water and undeformed ice, and (2) ridged ice and brash ice. The data further showed illustrative examples of SAR imagery over sea ice.

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.

scholarly journals RASF and DEDR-POCS Image Fusion through Multi-layer Perceptron in SAR Imagery Systems

2019 ◽  
pp. 20-26
Author(s):  
Israel Yañez-Vargas ◽  
Joel Quintanilla-Domínguez ◽  
Gabriel Aguilera-Gonzalez
Keyword(s):  
Synthetic Aperture Radar ◽  
Image Fusion ◽  
Low Cost ◽  
Synthetic Aperture ◽  
Discrete Wavelet ◽  
Multi Layer Perceptron ◽  
Robust Adaptive ◽  
Sar Imagery ◽  
Design Regularization ◽  
Aperture Radar

This paper presents a novel multi-layer perceptron (MLP) based image fusion technique, which fuses two synthetic aperture radar (SAR) images, obtained from the same spatial reflectivity map, acquired with a conventional low-cost fractional synthetic aperture radar (Fr-SAR) system, enhanced via two different methodologies. The first image is enhanced using the traditional descriptive experiment design regularization (DEDR) framework through the projection onto convex solution sets (POCS) method; the second image is enhanced with the DEDR framework by incorporating the robust adaptive spatial filtering (RASF) solution operator. This work describes a MLP based technique applied to the pixel level multi-focus fusion problem characterized by the use of image windows with the idea of reducing noise and determining which pixel is clearer between the two images. Experimental results show that the proposed novel method outperforms the discrete wavelet transform based most competing approach.

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