基于森林密度的相位与幅度联合反演算法

Phase and Amplitude of Joint Inversion Based on Forest Density

森林树高的反演是极化干涉合成孔径雷达(polarimetric SAR interferometry,PolInSAR)领域研究的热点。已有研究表明森林密度会对树高反演精度产生较大影响,但传统算法没有考虑森林密度的影响。针对这一现象,首先利用模拟数据分析森林密度对传统森林树高反演算法的影响;然后根据影响的特点提出一种基于森林密度的相位与幅度联合反演算法;最后采用德国宇航局与瑞典国防研究局机载E-SAR系统获取的PolInSAR数据对文中所用算法进行了实验分析。结果表明,该算法比传统算法反演精度更高,验证了算法的可靠性和有效性。由此可见,森林密度是森林重要的森林物理参数,通过引入森林密度,明显提升了树高反演的效果,说明引入密度参数的重要性。

Inversion of forest tree height is a hotspot in the field of polarimetric SAR interferometry(PolInSAR).Previous studies have shown that forest density has a great impact on the accuracy of tree height inversion,but traditional algorithms do not consider the impact of forest density.In view of this phenomenon,this paper uses simulation data to analyze the impact of forest density on traditional forest height inversion algorithm,and then proposes a phase and amplitude joint inversion algorithm based on forest density according to the characteristics of the impact.Finally,the algorithm in this paper is tested and analyzed by using PolInSAR data acquired by Deutsches Zentrum für Luft-und Raumfahrt(DLR)and Swedish Defense Research Agency(FOI)airborne E-SAR system.The results show that the inversion accuracy of the proposed algorithm is higher than that of the traditional algorithm,which verifies the reliability and effectiveness of the algorithm.It can be seen that forest density is an important forest physical parameter.By introducing forest density,the effect of tree height inversion is obviously improved,which shows the importance of introducing density parameters.