DECOMPOSITION METHODS FOR THE ESTIMATION OF BARE SOIL SURFACE PARAMETERS USING FULLY POLARIMETRIC SAR DATA

被引：1

作者：

Yuan, Weilin ^{[1
]}

Qin, Qiming ^{[1
]}

Du, Shihong ^{[1
]}

Shen, Xinyi ^{[1
]}

Jiang, Hongbo ^{[1
]}

Ma, Yan ^{[1
]}

Liu, Shixiong ^{[1
]}

机构：

[1] Peking Univ, Inst Remote Sensing & GIS, Beijing 100871, Peoples R China

来源：

2010 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2010年

关键词：

Bare soil surface parameters; Polarimetric target decomposition; Synthetic Aperture Radar (SAR); Advanced Integral Equation Model (AIEM); CLASSIFICATION; THEOREMS; MODEL;

D O I：

10.1109/IGARSS.2010.5653057

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

This study wants to demonstrate that two different polarimetric target decomposition methods can improve SAR data accuracy for estimating the parameters of bare soil surface. To achieve this goal, two experiments are conducted: (1) both Freeman and Cloude decomposition methods are performed on JPL/AIRSAR L-band fully polarimetric data; and (2) Advanced Integral Equation Model (AIEM) is used to simulate backscatting coefficients. The root mean square errors (RMSEs) of sigma(0)(hh), sigma(0)(vv) between original data and AIEM simulated data are 1.96 and 1.25 dB. However, if Cloude method is used to decompose original data, the RMSEs will be reduced to 1.45 and 1.14dB, respectively; for Freeman method, the RMSEs are 1.64 and 1.35 dB. Therefore, polarimetric target decomposition compensation, especially Cloude method, can help to improve the accuracy of SAR data for estimating the parameters of bare soil surface.

引用

页码：1273 / 1276

页数：4

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