Greenland Observed At High Resolution By The Seasat Scatterometer

Long, D.G.; Hardin, Perry J.; Shaw, R. Anthony

doi:10.1109/igarss.1992.576703

Cited by 13 publications

(10 citation statements)

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“…This is particularly true for instance in the north-east dry snow zone, and is seen in SASS data [5]. Thus we suggest that time series of multiple frequency enhanced resolution A images and their associated B values, offer greater potential for retrieving snow accumulation than single channel, fixed incidence angle instrument data.…”

Section: Decadal Changementioning

confidence: 88%

“…As a result the two are indistinguishable, and the radar senses only a broad 'ablation zone' [5]. Near the ice sheet margins, the surface autocorrelation function determines A and B by surface scattering, and the roughness scale causes greater backscattering at Ku-band than C-band of up to 8 dB in Fig.…”

Section: Interannual Ice Sheet Variabilitymentioning

confidence: 99%

“…Meltwater alters the surface reflection or transmissivity, limiting subsurface volume scattering effects by increasing absorption and extinction. In addition, (T* is influenced by layering which results from seasonal snow accumulation and melt patterns [5]. The spatial extent of summer melt appears as low (T" values around the lower elevation fringe of the ice sheet, particularly on day 209.…”

Section: Interannual Ice Sheet Variabilitymentioning

confidence: 99%

“…Briefly in 1978, and since 1991, microwave radar has been used to study relationships between snow and ice surface structure and backscatter characteristics [3,41. Using this information radar data is used to map the relative size and locations of ice sheet physical zones or 'facies' [5,6].…”

Section: Introductionmentioning

confidence: 99%

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Seasat, ERS-1/2 and NSCAT scatterometer observed changes on the large ice sheets

Drinkwater

Long²

1998

IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings.

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-Satellite-borne wind scatterometers are effective tools for monitoing ice sheets and microwave imaging techniques enable comparison of historic and contemporary scatterometer data in climate change studies. We document scattering characteristics of the Greenland ice sheet using data from the NSCAT, ERS-112 and Seasat SASS instruments. C-and Ku-band data enable characterization of frequencydependent scattering characteristics and regional melting delineation. SASS-NSCAT differences show 18 year changes in dry-snow zone extent and indicate the decadal reponse to changes in the spatial patterns of accumulation and ablation.

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Section: Decadal Changementioning

confidence: 88%

Section: Interannual Ice Sheet Variabilitymentioning

confidence: 99%

Section: Interannual Ice Sheet Variabilitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Seasat, ERS-1/2 and NSCAT scatterometer observed changes on the large ice sheets

Drinkwater

Long²

1998

IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings.

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“…Originally designed for retrieval of near-surface winds over the ocean, scatterometer data is also being applied to the study of tropical vegetation, polar ice, and global change 26,29,33,34,59 . Like radiometer data, scatterometer data is operationally used in weather forecasting and sea-ice monitoring.…”

Section: Spaceborne Microwave Sensorsmentioning

confidence: 99%

Reconstruction and Resolution Enhancement Techniques for Microwave Sensors

Long¹,

Chen²

2003

Frontiers of Remote Sensing Information Processing

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Microwave remote sensing instruments such as radiometers and scatterometers have proven themselves effective in a variety of Earth Science studies. The resolution of these sensors, while adequate for many applications, is a limiting factor to their application in other studies. As a result, there is a strong interest in developing ground processing methods which can enhance the spatial resolution of the data. A number of resolution enhancement algorithms have been developed based on inverse filtering and irregular sampling reconstruction. This Chapter discusses the use of resolution enhancement and reconstruction algorithms in microwave remote sensing. While the focus is on microwave instruments, the techniques and algorithms considered are applicable to a variety of sensors, including those not originally designed for imaging.

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