Discrimination of glacier facies using multi-temporal SAR data

Partington, K.C.

doi:10.1017/s0022143000002331

Cited by 86 publications

(68 citation statements)

References 12 publications

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“…At 6.9 GHz, observed brightness temperature results from the emission in the upper tens of meters (Surdyk, 1995;Surdyk, 2002). Penetration depth at 5.3 GHz is also estimated of the order of tens of meters in dry polar firn (Partington, 1998;Bingham and Drinkwater, 2000). Depending on the annual SMB, dense layers in the first tens of meters have formed a few years up to decades ago.…”

Section: Snow Melting Areas and Microwave Signaturementioning

confidence: 93%

Snow melting bias in microwave mapping of Antarctic snow accumulation

et al. 2008

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Abstract. Satellite records of microwave surface emission have been used to interpolate in-situ observations of Antarctic surface mass balance (SMB) and build continental-scale maps of accumulation. Using a carefully screened subset of SMB measurements in the 90 • -180 • E sector, we show a reasonable agreement with microwave-based accumulation map in the dry-snow regions, but large discrepancies in the coastal regions where melt occurs during summer. Using an emission microwave model, we explain the failure of microwave sensors to retrieve SMB by the presence of layers created by melt/refreeze cycles. We conclude that regions potentially affected by melting should be masked-out in microwave-based interpolation schemes.

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Section: Snow Melting Areas and Microwave Signaturementioning

confidence: 93%

Snow melting bias in microwave mapping of Antarctic snow accumulation

et al. 2008

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“…This is found in all seasons [Partington, 1998]. Backscatter variations and some areas of higher backscatter within the dry-snow facies may be related to grain size variations, specifically large depth-hoar crystals forming due to strong temperature gradients in areas of lower accumulation [Partington, 1998]. [1992], also studying Greenland, see a distinct boundary at the percolation facies, the wet-snow facies being a bright area with dark patches (slush around surface lakes).…”

Section: Glacier Facies and Equilibrium Linementioning

confidence: 99%

“…[1992], also studying Greenland, see a distinct boundary at the percolation facies, the wet-snow facies being a bright area with dark patches (slush around surface lakes). Partington [1998] sees three zones within the percolation and wet-snow facies. At high elevations a high backscatter is found in all seasons because hardly any melt is present.…”

Section: Glacier Facies and Equilibrium Linementioning

confidence: 99%

Measuring snow and glacier ice properties from satellite

König¹,

Winther²,

Isaksson³

2001

Reviews of Geophysics

246

159

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Abstract. Satellite remote sensing is a convenient tool for studying snow and glacier ice, allowing us to conduct research over large and otherwise inaccessible areas. This paper reviews various methods for measuring snow and glacier ice properties with satellite remote sensing. These methods have been improving with the use of new satellite sensors, like the synthetic aperture radar (SAR) during the last decade, leading to the development of new and powerful methods, such as SAR interferometry for glacier velocity, digital elevation model generation of ice sheets, or snow cover mapping. Some methods still try to overcome the limitations of present sensors, but future satellites will have much increased capability, for example, the ability to measure the whole optical spectrum or SAR sensors with multiple polarization or frequencies. Among the methods presented are the satellite-derived determination of surface albedo, snow extent, snow volume, snow grain size, surface temperature, glacier facies, glacier velocities, glacier extent, and ice sheet topography. In this review, emphasis is put on the principles and theory of each satellite remote sensing method. An extensive list of references, with an emphasis on studies from the 1990s, allows the reader to delve into specific topics. INTRODUCTIONThere have been tremendous technological achievements in the twentieth century that enable scientists to undertake research at virtually every spot on Earth. In parallel, advances in space technology during the last decades have provided us with a rapidly increasing number of satellite platforms that can be used to study complex physical processes of the Earth-atmosphere system. The development within this field concerns not only the growing number of satellites but also the rapid progression of sensor capabilities. In the future a major challenge will be connected with combining various sources of information gathered from space, i.e., data assimilation, and to make use of this information in a systematic, repetitive manner to monitor temporal and spatial variability, for example, in climate-change research.In the field of glaciology, satellite remote sensing has proven to be a particularly useful tool because areas of interest are often inaccessible. Further, in many regions at high latitudes, like the Greenland and Antarctic ice sheets, it is only during parts of the year that effective ground-based research can be carried out due to the harsh climate environment and the lack of daylight. Satellite remote sensing often permits real-time, yearround, and long-term studies. Also, the large spatial coverage of satellite remotely sensed data enables monitoring and process studies over large areas. In this way, satellite data help in understanding processes and teleconnections on the regional, continental, or even global scale, for example, global satellite-derived maps of snow cover. Such products are particularly important because they assist interpretation and analysis concerning global change.Also, on smaller scales, sate...

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“…A possible explanation of the temporal backscatter variability for the Devon ice cap is the formation of surface hoar. A backscatter increase of 5 dB has been observed in relation to the development of hoar frost on ice caps in Alaska (Partington, 1998). Surface hoar is a layer of ice crystals from 1 mm to 10 mm in size that grows on a snow surface under certain conditions.…”

Section: Resultsmentioning

confidence: 99%