• Korean Journal of Remote Sensing
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• v.17 no.2
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• pp.141-153
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• 2001

A semi-empirical polarimetric backscattering model for bare soil surfaces is presented. Based on measurements by using polarimetric scatterometers and the JPL AirSAR, as well as the theoretical models, the backscattering coefficints $\sigma$$^0_w$, $\sigma$$^0_{hh}$ and $\sigma$$^0_{vh}$, and the parameters of the copolarized phase-difference probability density function, namely the degree of correlation $\alpha$ and the copolarized-phase-difference $\zeta$, are modeled empirically in terms of the volumetric soil moisture content m$_v$ and the surface roughness parameters $k_s$ and $k_l$, where k=2$\pi$f/c, s is the rms height and l is the correlation length.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.12
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• pp.1345-1351
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• 2007

This paper proposes a polarimetric SAR image classification technique based on the degree of poarization(DoP) and copolarized phase-difference(CPD) statistics. At first, the formulation for the DoP and CPD is derived. Then, the classification technique is verified with the SAR full polarimetric L-band data with consideration of exceptional cases. The technique has capability of classifying SAR data into four major classes, such as bare surface, short-vegetation canopy, tall-vegetation canopy, and village.

• Korean Journal of Remote Sensing
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• v.26 no.1
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• pp.1-7
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• 2010

This paper proposes a new decomposition technique for polarimetric synthetic aperture radar (SAR) images. This new decomposition technique is based on the degree of polarization (DoP) and co-polarized phase-difference (CPD) of the measured polarimetric backscattering coefficients. This decomposition technique is compared with the existing three- and four-component decomposition techniques with the ALOS PALSAR full polarimetric L-band data acquired in 2009. It is shown that the new decomposition technique is better or comparable to the existing techniques for the study areas such as sea, bare soil, forest, and urban area.