In Search of the Statistical Properties of High-Resolution Polarimetric SAR Data for the Measurements of Forest Biomass Beyond the RCS Saturation Limits
In Search of the Statistical Properties of High-Resolution Polarimetric SAR Data for the Measurements of Forest Biomass Beyond the RCS Saturation Limits
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DOI：
10.1109/lgrs.2006.878299
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发表时间：
2006-10
影响因子：
4.8
通讯作者：
Haipeng Wang;K. Ouchi;Manabu Watanabe;M. Shimada;T. Tadono;A. Rosenqvist;S. Romshoo;M. Matsuoka;T. Moriyama;S. Uratsuka
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文献类型：
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作者：
Haipeng Wang;K. Ouchi;Manabu Watanabe;M. Shimada;T. Tadono;A. Rosenqvist;S. Romshoo;M. Matsuoka;T. Moriyama;S. Uratsuka
这封信的目的是介绍搜索有效的参数，描述高分辨率合成孔径雷达（SAR）图像和森林参数之间的关系的研究结果。研究是基于非高斯纹理分析的极化机载Pi-SAR数据在针叶林在北海道，日本。首先分析了森林生物量的雷达散射截面（RCS）。据发现，L-波段RCS稳步增加的生物量和饱和约40吨/公顷。这些结果与先前的研究相似。图像振幅的概率密度函数，然后调查，瑞利，对数正态分布，威布尔，和K-分布，K-分布被认为是最适合所有极化的L-波段数据，虽然威布尔分布同样适合。此外，树木的生物量和顺序参数的K-分布在交叉偏振图像之间的相关性被发现是非常高的，和顺序参数增加一致的生物量约100吨/公顷，这是远远超出了L-波段RCS的饱和极限。因此，K分布的序参量可以作为一个新的参数，在比传统的RCS方法更宽的范围内从高分辨率极化SAR数据中估计森林生物量
The purpose of this letter is to present the results on the study of searching effective parameters that describe the relation between high-resolution synthetic aperture radar (SAR) images and forest parameters. The study is based on the non-Gaussian texture analysis of the polarimetric airborne Pi-SAR data over coniferous forests in Hokkaido, Japan. The radar cross section (RCS) in terms of a forest biomass is first analyzed. It is found that the L-band RCS increases steadily with the biomass and saturates at approximately 40 tons/ha. These results are similar to the previous studies. The probability density function of the image amplitude is then investigated, and among Rayleigh, log-normal, Weibull, and K-distributions, the K-distribution is found to fit best to the L-band data of all polarizations, although the Weibull distribution fits equally well. Further, the correlation between the tree biomass and the order parameter of the K-distribution in the cross-polarization images is found to be very high, and the order parameter increases consistently with the biomass to approximately 100 tons/ha, which is well beyond the saturation limit of the L-band RCS. Thus, the order parameter of the K-distribution can be a promising new parameter to estimate the forest biomass from high-resolution polarimetric SAR data in a much wider range than the conventional RCS method