scholarly journals The Separation of Sea-Ice Types in Radar Imagery (Abstract)

1987 ◽  
Vol 9 ◽  
pp. 247
Author(s):  
Benjamin Holt ◽  
F.D. Carsey
Keyword(s):  
Surface Morphology ◽  
Sea Ice ◽  
Open Water ◽  
Classification Algorithm ◽  
First Year ◽  
Volume Scattering ◽  
Radar Imagery ◽  
L Band ◽  
Sar Imagery ◽  
Scale Surface

The ability to distinguish the several major types of sea ice with active radar instruments has been well studied in recent years. The separation of sea-ice types by radar results principally from variations in radar back-scatter due to characteristic differences of these ice types in surface morphology and brine content. When sea ice is viewed with an active radar at angles greater than about 20° from nadir, undeformed ice reflects radar waves and results in a low return, while ridges, hummocks, and small-scale surface features scatter the radar waves and produce a high return. The presence of salt increases the dielectric constant of ice; penetration by radar into the ice is then negligible, and the return is essentially determined by surface morphology. The absence of salt reduces the dielectric properties of ice; radar waves can then penetrate the ice to some depth and are scattered by air bubbles and brine-drainage channels (called volume scattering), thereby enhancing the return even for roughened surfaces. All these properties vary significantly with radar frequency and polarization as well as seasonally. For example, higher radar frequencies respond to smaller-scale surface features, while lower radar frequencies penetrate further into the ice with resulting volume scattering. The high-resolution imagery from synthetic aperture radars (SAR), mounted on aircraft, shuttle, or satellite platforms, is very effective for many sea-ice studies, including the separation of ice types. An aircraft-mounted X-band (9 GHz) SAR, for example, can discriminate smooth first-year ice, rough first-year ice, multi-year ice, and open water by the intensity (tone) of the radar returns and floe geometry. The preferred SARs to date for satellites and shuttle platforms have been L-band (1–2 GHz) systems. SAR imagery of sea ice was extensively acquired by Seasat in 1978 over the Beaufort Sea, with limited quantities obtained by the Shuttle Imaging Radar (SIR-B) over the Weddell Sea in 1984. While L-band SAR can discriminate rough and smooth ice along with roughened open water based on image intensity and floe geometry, the returns from thick first-year ice and multi-year ice are not clearly distinguishable. The fact that there is volume scattering from multi-year ice suggests that there may be textural or spatial frequency variations that could be used to separate these two major ice types in radar imagery. In order to investigate the separation of sea-ice types in the large amount of L-band SAR imagery available, image-analysis techniques including filtering and classification programs have been utilized, pointing towards an automatic classification algorithm for use in future SAR sea-ice data sets, especially from space. An important characteristic of all SAR imagery is the presence of image speckle, a coherent form of noise caused by the random variability of scatterers across even a uniform surface. Most SAR processors reduce this effect by averaging multiple independent samples but this is done at the cost of reducing resolution. Speckle reduction can also be accomplished by filtering. Several filters have been tested including median, box, and adaptive edge filters. Each filter has different characteristics in terms of smoothing speckle and in the response to sharp gradients or edges, such as ridge or lead openings, as well as computational requirements. Optimization of each filter’s parameters has been determined by the quality of classification of each ice type. The classification programs that have been tested are based on tone and texture image characteristics. The programs are supervised; that is, a small training area for each class is pre-selected for statistical analysis. From these statistics, the remainder of the imagery is subjected to the particular classification algorithm. The tone program separates classes based on the mean, standard deviation, and number of standard deviations of each class, and includes a Bayesian maximum-likelihood classifier for ambiguous elements. The texture program determines the statistical homogeneity of each class and the optimal segmentation of each small area into the various classes.

scholarly journals The Separation of Sea-Ice Types in Radar Imagery (Abstract)

1987 ◽  
Vol 9 ◽  
pp. 247-247
Author(s):  
Benjamin Holt ◽  
F.D. Carsey
Keyword(s):  
Surface Morphology ◽  
Sea Ice ◽  
Open Water ◽  
Classification Algorithm ◽  
First Year ◽  
Volume Scattering ◽  
Radar Imagery ◽  
L Band ◽  
Sar Imagery ◽  
Scale Surface

The ability to distinguish the several major types of sea ice with active radar instruments has been well studied in recent years. The separation of sea-ice types by radar results principally from variations in radar back-scatter due to characteristic differences of these ice types in surface morphology and brine content. When sea ice is viewed with an active radar at angles greater than about 20° from nadir, undeformed ice reflects radar waves and results in a low return, while ridges, hummocks, and small-scale surface features scatter the radar waves and produce a high return. The presence of salt increases the dielectric constant of ice; penetration by radar into the ice is then negligible, and the return is essentially determined by surface morphology. The absence of salt reduces the dielectric properties of ice; radar waves can then penetrate the ice to some depth and are scattered by air bubbles and brine-drainage channels (called volume scattering), thereby enhancing the return even for roughened surfaces. All these properties vary significantly with radar frequency and polarization as well as seasonally. For example, higher radar frequencies respond to smaller-scale surface features, while lower radar frequencies penetrate further into the ice with resulting volume scattering.The high-resolution imagery from synthetic aperture radars (SAR), mounted on aircraft, shuttle, or satellite platforms, is very effective for many sea-ice studies, including the separation of ice types. An aircraft-mounted X-band (9 GHz) SAR, for example, can discriminate smooth first-year ice, rough first-year ice, multi-year ice, and open water by the intensity (tone) of the radar returns and floe geometry. The preferred SARs to date for satellites and shuttle platforms have been L-band (1–2 GHz) systems. SAR imagery of sea ice was extensively acquired by Seasat in 1978 over the Beaufort Sea, with limited quantities obtained by the Shuttle Imaging Radar (SIR-B) over the Weddell Sea in 1984. While L-band SAR can discriminate rough and smooth ice along with roughened open water based on image intensity and floe geometry, the returns from thick first-year ice and multi-year ice are not clearly distinguishable. The fact that there is volume scattering from multi-year ice suggests that there may be textural or spatial frequency variations that could be used to separate these two major ice types in radar imagery. In order to investigate the separation of sea-ice types in the large amount of L-band SAR imagery available, image-analysis techniques including filtering and classification programs have been utilized, pointing towards an automatic classification algorithm for use in future SAR sea-ice data sets, especially from space.An important characteristic of all SAR imagery is the presence of image speckle, a coherent form of noise caused by the random variability of scatterers across even a uniform surface. Most SAR processors reduce this effect by averaging multiple independent samples but this is done at the cost of reducing resolution. Speckle reduction can also be accomplished by filtering. Several filters have been tested including median, box, and adaptive edge filters. Each filter has different characteristics in terms of smoothing speckle and in the response to sharp gradients or edges, such as ridge or lead openings, as well as computational requirements. Optimization of each filter’s parameters has been determined by the quality of classification of each ice type.The classification programs that have been tested are based on tone and texture image characteristics. The programs are supervised; that is, a small training area for each class is pre-selected for statistical analysis. From these statistics, the remainder of the imagery is subjected to the particular classification algorithm. The tone program separates classes based on the mean, standard deviation, and number of standard deviations of each class, and includes a Bayesian maximum-likelihood classifier for ambiguous elements. The texture program determines the statistical homogeneity of each class and the optimal segmentation of each small area into the various classes.

scholarly journals Dual Frequency Radar Ice and Snow Signatures

1983 ◽  
Vol 29 (102) ◽  
pp. 286-295
Author(s):  
R. D. Ketchum
Keyword(s):  
Sea Ice ◽  
Sea Water ◽  
Open Water ◽  
Good Choice ◽  
Signal Loss ◽  
Dual Frequency ◽  
X Band ◽  
Radar Imagery ◽  
High Backscatter ◽  
L Band

AbstractDual frequency (X-band and L-band) synthetic-aperture radar imagery of sea ice is examined to show the differences between the bands and their complementary nature for resolving ambiguities in interpretation. High backscatter at X-band from visibly smooth thin ice is not observed at L-band. One hypothesis is that the high X-band backscatter may be caused by a reflective layer at the snow/ice interface. A second hypothesis is that the high X-band backscatter may be caused by moisture in the snow. A third hypothesis states that the phenomenon may be due to snow flowers. High backscatter at L-band is observed for slush on open water. The return is very weak at X-band, thus allowing distinction of slush by comparing L-band and X-band images. High intensity, but only partial returns from icebergs at L-band have been observed. The hypothesis is that internal iceberg/sea-water reflections are occurring. Some signals are directed away from the antenna, other reinforced signals are returned, producing very bright images. Occasionally, time-delayed signals are returned causing a false image at far range from the iceberg. The conclusion is that L-band is a poor choice for studies of iceberg distribution and size, but a good choice for iceberg detection because of the high reinforced returns from many icebergs and the low return from the adjacent sea ice. The penetration and subsequent signal loss of L-band in glacial ice, when compared to high X-band returns, may be useful to map glacierized land masses.

scholarly journals Winter Sea-ice mapping from multi-parameter synthetic-aperture radar data

1994 ◽  
Vol 40 (134) ◽  
pp. 31-45 ◽  
Author(s):  
Eric Rignot ◽  
Mark R. Drinkwater
Keyword(s):  
Sea Ice ◽  
Classification Accuracy ◽  
Open Water ◽  
Radar Data ◽  
Single Frequency ◽  
First Year ◽  
Synthetic Aperture Radar Data ◽  
Ice Conditions ◽  
L Band ◽  
Single Polarization

AbstractThe limitations of current and immediate future single-frequency, single-polarization, space-borne SARs for winter sea-ice mapping are quantitatively examined, and improvements are suggested by combining frequencies and polarizations. Ice-type maps are generated using multi-channel, air-borne SAR observations of winter sea ice in the Beaufort Sea to identify six ice conditions: (1) multi-year sea ice; (2) compressed first-year ice; (3) first-year rubble and ridges; (4) first-year rough ice; (5) first-year smooth ice; and (6) first-year thin ice. At a single polarization, C- (λ = 5.6 cm) and L- (λ = 24 cm) band frequencies yield a classification accuracy of 67 and 71%, because C-band confuses multi-year ice and compressed, rough, thick first-year ice surrounding multi-year ice floes, and L-band confuses multi-year ice and deformed first-year ice. Combining C- and L-band improves classification accuracy by 20%. Adding a second polarization at one frequency only improves classification accuracy by 10–14% and separates thin ice and calm open water. Under similar winter-ice conditions, ERS-1 (Cvv) and Radarsat (CHH) would overestimate the multi-year ice fraction by 15% but correctly map the spatial variability of ice thickness; J-ERS-1 (LHH) would perform poorly;and J-ERS-1 combined with ERS-1 or Radarsat would yield reliable estimates of the old, thick, first-year and thin-ice fractions, and of the spatial distribution of ridges. With two polarizations, future single-frequency space-borne SARs could improve our current capability to discriminate thinner ice types.

scholarly journals Dual Frequency Radar Ice and Snow Signatures

1983 ◽  
Vol 29 (102) ◽  
pp. 286-295 ◽  
Author(s):  
R. D. Ketchum
Keyword(s):  
Sea Ice ◽  
Sea Water ◽  
Open Water ◽  
Good Choice ◽  
Signal Loss ◽  
Dual Frequency ◽  
X Band ◽  
Radar Imagery ◽  
High Backscatter ◽  
L Band

Abstract Dual frequency (X-band and L-band) synthetic-aperture radar imagery of sea ice is examined to show the differences between the bands and their complementary nature for resolving ambiguities in interpretation. High backscatter at X-band from visibly smooth thin ice is not observed at L-band. One hypothesis is that the high X-band backscatter may be caused by a reflective layer at the snow/ice interface. A second hypothesis is that the high X-band backscatter may be caused by moisture in the snow. A third hypothesis states that the phenomenon may be due to snow flowers. High backscatter at L-band is observed for slush on open water. The return is very weak at X-band, thus allowing distinction of slush by comparing L-band and X-band images. High intensity, but only partial returns from icebergs at L-band have been observed. The hypothesis is that internal iceberg/sea-water reflections are occurring. Some signals are directed away from the antenna, other reinforced signals are returned, producing very bright images. Occasionally, time-delayed signals are returned causing a false image at far range from the iceberg. The conclusion is that L-band is a poor choice for studies of iceberg distribution and size, but a good choice for iceberg detection because of the high reinforced returns from many icebergs and the low return from the adjacent sea ice. The penetration and subsequent signal loss of L-band in glacial ice, when compared to high X-band returns, may be useful to map glacierized land masses.

scholarly journals Winter Sea-ice mapping from multi-parameter synthetic-aperture radar data

1994 ◽  
Vol 40 (134) ◽  
pp. 31-45 ◽  
Author(s):  
Eric Rignot ◽  
Mark R. Drinkwater
Keyword(s):  
Sea Ice ◽  
Classification Accuracy ◽  
Open Water ◽  
Radar Data ◽  
Single Frequency ◽  
First Year ◽  
Synthetic Aperture Radar Data ◽  
Ice Conditions ◽  
L Band ◽  
Single Polarization

AbstractThe limitations of current and immediate future single-frequency, single-polarization, space-borne SARs for winter sea-ice mapping are quantitatively examined, and improvements are suggested by combining frequencies and polarizations. Ice-type maps are generated using multi-channel, air-borne SAR observations of winter sea ice in the Beaufort Sea to identify six ice conditions: (1) multi-year sea ice; (2) compressed first-year ice; (3) first-year rubble and ridges; (4) first-year rough ice; (5) first-year smooth ice; and (6) first-year thin ice. At a single polarization, C- (λ = 5.6 cm) and L- (λ = 24 cm) band frequencies yield a classification accuracy of 67 and 71%, because C-band confuses multi-year ice and compressed, rough, thick first-year ice surrounding multi-year ice floes, and L-band confuses multi-year ice and deformed first-year ice. Combining C- and L-band improves classification accuracy by 20%. Adding a second polarization at one frequency only improves classification accuracy by 10–14% and separates thin ice and calm open water. Under similar winter-ice conditions, ERS-1 (Cvv) and Radarsat (CHH) would overestimate the multi-year ice fraction by 15% but correctly map the spatial variability of ice thickness; J-ERS-1 (LHH) would perform poorly;and J-ERS-1 combined with ERS-1 or Radarsat would yield reliable estimates of the old, thick, first-year and thin-ice fractions, and of the spatial distribution of ridges. With two polarizations, future single-frequency space-borne SARs could improve our current capability to discriminate thinner ice types.

scholarly journals Albedo of Young and First-Year Antarctic Sea Ice

1990 ◽  
Vol 14 ◽  
pp. 331 ◽  
Author(s):  
Richard Brandt ◽  
Ian Allison ◽  
Stephen Warren
Keyword(s):  
Sea Ice ◽  
Radiation Flux ◽  
Open Water ◽  
First Year ◽  
Spectral Measurements ◽  
Antarctic Sea Ice ◽  
Antarctic Expedition ◽  
Downward Radiation ◽  
Radiation Measurements ◽  
Snow Thickness

Reflection of solar radiation was studied in the seasonal sea-ice zone off East Antarctica on a cruise of the Australian Antarctic Expedition, October-December 1988. Spectral and total albedos were measured for grease ice, nilas, young grey ice, grey-white ice, snow-covered ice, and open water. Spectral measurements covered the region 400–1000 nm wavelength. For ice too thin to support our weight, the radiometers were mounted at the end of a 1.5 m rod extended out the door of a helicopter or from a basket hung from the ship's crane, using a positioning and leveling rack. Corrections had to be applied to the downward radiation flux because the helicopter or the crane was in the field of view of the cosine-collector. The fractional coverage of each of the ice types (and open water) was estimated hourly for the region near the ship, as well as the thickness of each ice type, and the snow thickness. Observations were carried out continuously during the four weeks the ship was in the ice, supplemented by occasional helicopter surveys covering larger areas. These observations, together with the radiation measurements, make possible the computation of area-average albedo for the East Antarctic sea-ice zone in spring.

scholarly journals Effects of decimetre-scale surface roughness on L-band Brightness Temperature of Sea Ice

2019 ◽  
Author(s):  
Maciej Miernecki ◽  
Lars Kaleschke ◽  
Nina Maaß ◽  
Stefan Hendricks ◽  
Sten Schmidl Søbjrg
Keyword(s):  
Surface Roughness ◽  
Sea Ice ◽  
Brightness Temperature ◽  
Large Scale ◽  
Ice Thickness ◽  
Emission Model ◽  
Vertical Polarization ◽  
Sea Ice Thickness ◽  
L Band ◽  
Scale Surface

Abstract. Sea ice thickness measurements with L-band radiometry is a technique which allows daily, weather-independent monitoring of the polar sea ice cover. The sea-ice thickness retrieval algorithms relay on the sensitivity of the L-band brightness temperature to sea-ice thickness. In this work, we investigate the decimetre-scale surface roughness as a factor influencing the L-band emissions from sea ice. We used an airborne laser scanner to construct a digital elevation model of the sea ice surface. We found that the probability density function of surface slopes is exponential for a range of degrees of roughness. Then we applied the geometrical optics, bounded with the MIcrowave L-band LAyered Sea ice emission model in the Monte Carlo simulation to simulate the effects of surface roughness. According to this simulations, the most affected by surface roughness is the vertical polarization around Brewster's angle, where the decrease in brightness temperature can reach 8 K. The vertical polarization for the same configuration exhibits a 4 K increase. The near-nadir angles are little affected, up to 2.6 K decrease for the most deformed ice. Overall the effects of large-scale surface roughness can be expressed as a superposition of two factors: the change in intensity and the polarization mixing. The first factor depends on surface permittivity, second shows little dependence on it. Comparison of the brightness temperature simulations with the radiometer data does not yield definite results.

scholarly journals Albedo of the ice covered Weddell and Bellingshausen Seas

2012 ◽  
Vol 6 (2) ◽  
pp. 479-491 ◽  
Author(s):  
A. I. Weiss ◽  
J. C. King ◽  
T. A. Lachlan-Cope ◽  
R. S. Ladkin
Keyword(s):  
Sea Ice ◽  
Surface Albedo ◽  
Austral Summer ◽  
Open Water ◽  
Weddell Sea ◽  
First Year ◽  
Pack Ice ◽  
Bellingshausen Sea ◽  
The Mean ◽  
The Antarctic

Abstract. This study investigates the surface albedo of the sea ice areas adjacent to the Antarctic Peninsula during the austral summer. Aircraft measurements of the surface albedo, which were conducted in the sea ice areas of the Weddell and Bellingshausen Seas show significant differences between these two regions. The averaged surface albedo varied between 0.13 and 0.81. The ice cover of the Bellingshausen Sea consisted mainly of first year ice and the sea surface showed an averaged sea ice albedo of αi = 0.64 ± 0.2 (± standard deviation). The mean sea ice albedo of the pack ice area in the western Weddell Sea was αi = 0.75 ± 0.05. In the southern Weddell Sea, where new, young sea ice prevailed, a mean albedo value of αi = 0.38 ± 0.08 was observed. Relatively warm open water and thin, newly formed ice had the lowest albedo values, whereas relatively cold and snow covered pack ice had the highest albedo values. All sea ice areas consisted of a mixture of a large range of different sea ice types. An investigation of commonly used parameterizations of albedo as a function of surface temperature in the Weddell and Bellingshausen Sea ice areas showed that the albedo parameterizations do not work well for areas with new, young ice.

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