Effect of topography on SAR calibration

Zyl, J.J. van; Shi, Jiancheng

doi:10.1117/12.140622

Cited by 27 publications

(35 citation statements)

References 4 publications

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“…In this study, 30 m resolution DEM data were used to correct terrain-induced distortions in the Radarsat-2 data. Based on the method introduced by van Zyl [31], the backscattering coefficient of the SAR image was corrected to a reference surface:…”

Section: Radarsat-2 Datamentioning

confidence: 99%

A Synergistic Methodology for Soil Moisture Estimation in an Alpine Prairie Using Radar and Optical Satellite Data

Xing

Bai

2014

Remote Sensing

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This paper presents a microwave/optical synergistic methodology to retrieve soil moisture in an alpine prairie. The methodology adequately represents the scattering behavior of the vegetation-covered area by defining the scattering of the vegetation and the soil below. The Integral Equation Method (IEM) was employed to determine the backscattering of the underlying soil. The modified Water Cloud Model (WCM) was used to reduce the effect of vegetation. Vegetation coverage, which can be easily derived from optical data, was incorporated in this method to account for the vegetation gap information. Then, an inversion scheme of soil moisture was developed that made use of the dual polarizations (HH and VV) available from the quad polarization Radarsat-2 data. The method developed in this study was assessed by comparing the reproduction of the backscattering, which was calculated from an area with full vegetation cover to that with relatively sparse cover. The accuracy and sources of error in this soil moisture retrieval method were evaluated. The results showed a good correlation between the measured and estimated soil moisture (R 2 = 0.71, RMSE = 3.32 vol.%, p < 0.01). Therefore, this method has operational potential for estimating soil moisture under the vegetated area of an alpine prairie.

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Section: Radarsat-2 Datamentioning

confidence: 99%

A Synergistic Methodology for Soil Moisture Estimation in an Alpine Prairie Using Radar and Optical Satellite Data

Xing

Bai

2014

Remote Sensing

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“…The look-angle of JERS varies by a few degrees across its swath and the effect on scattering processes, particularly in forested areas, is to make a brighter signal return in the near-range than in the far-range, even after appropriate scattering-area calibration (Van Zyl, 1993;Van Zyl, Chapman, Dubois, & Shi, 1993). Thus, although crosscorrelation between JERS and ERS data was very successful in geometrically matching the scenes, where the far-range of one track was united to the near-range of another track within one ERS reference frame, the difference in image brightness along the image edges became very apparent.…”

Section: Jers Radiometric Matchingmentioning

confidence: 99%

Large-scale mapping of boreal forest in SIBERIA using ERS tandem coherence and JERS backscatter data

Wagner

Luckman

Vietmeier

et al. 2003

Remote Sensing of Environment

127

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Siberia's boreal forests represent an economically and ecologically precious resource, a significant part of which is not monitored on a regular basis. Synthetic aperture radars (SARs), with their sensitivity to forest biomass, offer mapping capabilities that could provide valuable up-to-date information, for example about fire damage or logging activity. The European Commission SIBERIA project had the aim of mapping an area of approximately 1 million km 2 in Siberia using SAR data from two satellite sources: the tandem mission of the European Remote Sensing Satellites ERS-1/2 and the Japanese Earth Resource Satellite JERS-1. Mosaics of ERS tandem interferometric coherence and JERS backscattering coefficient show the wealth of information contained in these data but they also show large differences in radar response between neighbouring images. To create one homogeneous forest map, adaptive methods which are able to account for brightness changes due to environmental effects were required. In this paper an adaptive empirical model to determine growing stock volume classes using the ERS tandem coherence and the JERS backscatter data is described. For growing stock volume classes up to 80 m 3 /ha, accuracies of over 80% are achieved for over a hundred ERS frames at a spatial resolution of 50 m. D

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“…Thus, when images, acquired by the same sensor at different incidence angles, are fused, since the received backscattered radiation is strongly depending on the angle and, thus, on the topography, it is necessary to apply radiometric corrections. This can be done by using a digital elevation model (DEM); a correction of the considered images can be exploited to obtain a real view of the observed scene [9,32,33].…”

Section: Fusion Of Multipolarization-multifrequency-multiresolution Smentioning

confidence: 99%

Image fusion techniques for remote sensing applications

et al. 2002

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Effect of topography on SAR calibration

Cited by 27 publications

References 4 publications

A Synergistic Methodology for Soil Moisture Estimation in an Alpine Prairie Using Radar and Optical Satellite Data

A Synergistic Methodology for Soil Moisture Estimation in an Alpine Prairie Using Radar and Optical Satellite Data

Large-scale mapping of boreal forest in SIBERIA using ERS tandem coherence and JERS backscatter data

Image fusion techniques for remote sensing applications

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