Resolution enhancement of spaceborne scatterometer data

Long, D.G.; Hardin, Perry J.; Whiting, P.T.

doi:10.1109/36.225536

Cited by 234 publications

(166 citation statements)

References 17 publications

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“…Theretore careful data selection must be performed prior to incidence angle response modeling. Data are selected using masks produced using the scatterometer image reconstruction (SIR) algorithm [Long et al, 1993]. SIR is a resolution enhancement algorithm based on spatial overlap of the measurements taken at nominal ble causes to explain this behavior have been examined and dismissed; however, there is one that could explain most of the ascending/descending observations.…”

Section: Calibration Data Setsmentioning

confidence: 99%

NSCAT normalized radar backscattering coefficient biases using homogenous land targets

Zec¹,

Long²,

Jones³

1999

J. Geophys. Res.

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Section: Calibration Data Setsmentioning

confidence: 99%

NSCAT normalized radar backscattering coefficient biases using homogenous land targets

Zec¹,

Long²,

Jones³

1999

J. Geophys. Res.

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“…The scatterometer image reconstruction with filter (SIRF) algorithm was developed to enhance scatterometer image resolution by combining data from multiple passes of the satellite [Long et al, 1993]. It uses multiple o values to increase the effective resolution of the data.…”

Section: Introductionmentioning

confidence: 99%

Sea ice extent mapping using Ku band scatterometer data

Remund¹,

Long²

1999

J. Geophys. Res.

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Abstract.Although spaceborne scatterometers such as the NASA scatterometer have inherently low spatial resolution, resolution enhancement techniques can be used to increase the utility of scatterometer data in monitoring sea-ice extent in the polar regions, a key parameter in the global climate. The resolution enhancement algorithm produces images of A and B, where A is the normalized radar backscatter coefficient o at 40Њ incidence and B is the incidence angle dependence of o . Dual-polarization A and B parameters are used to identify sea ice and ocean pixels in composite images. The A copolarization ratio and vertically polarized B are used as primary classification parameters to discriminate between sea ice and open ocean. Estimates of the sea-ice extent are obtained using linear and quadratic (Mahalanobis distance) discriminant boundaries. The distribution parameters needed for the quadratic estimate are taken from the linear estimate. The o error variance is used to reduce errors in the linear and Mahalanobis ice/ocean classifications. Noise reduction is performed through binary image region growing and erosion/dilation techniques. The resulting edge closely matches the NASA Team algorithm special sensor microwave imager derived 30% ice concentration edge. A 9-month data set of global sea-ice extent maps is produced with one 6-day average map every 3 days.

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“…The random orientation of individual scatterers in the vegetation canopy makes sigma-0 essentially polarization insensitive [18], while the equatorial location minimizes seasonal effects. The observed diurnal sigma-0 variation is within 0.5 dB, with the highest sigma-0 in the morning [18], [19]. In addition to the Amazon basin, another large area in central Russia was identified, during the calibration and validation (cal/val) activities, as being sufficiently homogeneous and isotropic.…”

Section: ) Beam Balancing Using Open Ocean Backscatter Measurementsmentioning

confidence: 83%

“…2) Beam Balancing Using Distributed Land Targets: Distributed land targets have been used for scatterometer beam balancing during SASS [18], [19] and ERS-1 [19] missions. This calibration method relies on large area homogeneous land targets with uniform azimuthal responses.…”

Section: ) Beam Balancing Using Open Ocean Backscatter Measurementsmentioning

confidence: 99%

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Postlaunch sensor verification and calibration of the NASA Scatterometer

Tsai

Graf

Winn

et al. 1999

IEEE Trans. Geosci. Remote Sensing

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Abstract-Scatterometer instruments are active microwave sensors that transmit a series of microwave pulses and measure the returned echo power to determine the normalized radar backscattering cross section (sigma-0) of the ocean surface from which the speed and direction of near-surface ocean winds are derived. The NASA Scatterometer (NSCAT) was launched on board the ADEOS spacecraft in August 1996 and returned ten months of high-quality data before the failure of the ADEOS spacecraft terminated the data stream in June 1997.The purpose of this paper is to provide an overview of the NSCAT instrument and sigma-0 computation and to describe the process and the results of an intensive postlaunch verification, calibration, and validation effort. This process encompassed the functional and performance verification of the flight instrument, the sigma-0 computation algorithms, the science data processing system, and the analysis of the sigma-0 and wind products. The calibration process included the radiometric calibration of NSCAT using both engineering telemetry and science data and the radiometric beam balance of all eight antenna beams using both open ocean and uniform land targets. Finally, brief summaries of the construction of the NSCAT geophysical model function and the verification and validation of the wind products will be presented.The key results of this paper are as follows: The NSCAT instrument was shown to function properly and all functional parameters were within their predicted ranges. The instrument electronics subsystems were very stable and all of the key parameters, such as transmit power, receiver gain, and bandpass filter responses, were shown to be stable to within 0.1 dB. The science data processing system was thoroughly verified and the sigma-0 computation error was shown to be less than 0.1 dB. All eight antenna beams were radiometrically balanced, using natural targets, to an estimated accuracy of about 0.3 dB. Finally, a new model function, called NSCAT-1, was constructed and used to produce wind products. The wind products were statistically verified using ECMWF wind fields and were validated using NDBC buoy measurements. Overall, we believe that NSCAT generated high-quality wind products with wind speed and direction accuracies that met the science requirements.

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Resolution enhancement of spaceborne scatterometer data

Cited by 234 publications

References 17 publications

NSCAT normalized radar backscattering coefficient biases using homogenous land targets

NSCAT normalized radar backscattering coefficient biases using homogenous land targets

Sea ice extent mapping using Ku band scatterometer data

Postlaunch sensor verification and calibration of the NASA Scatterometer

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