融合升降轨的极化干涉SAR三层模型植被高度反演方法

发布时间：2018-08-23 19:14

【摘要】：森林参数的获取不仅可以估算地表生物量和林下地形,还有助于研究全球碳循环和分析全球气候变化。极化干涉SAR植被参数反演算法一般是基于随机地体两层模型(RVoG),但是当实际植被有着冠层、树干层和地表层的明显三层结构时,植被参数反演精度就会变差;另外,由于机载SAR系统数据的近距远距垂直向波数差异较大,导致试验结果存在着由其引起的系统误差。针对这两个问题,本文提出了一种融合升降轨的极化干涉SAR三层模型植被参数反演方法。该方法首先采用三层植被RVoG模型修正微波在穿透植被时的散射过程;然后采用融合升降轨道数据的方式削弱其系统误差;最后,采用非线性迭代平差的反演算法来进行植被高度反演。为了验证该方法的有效性,采用了德国宇航局DLR提供的BioSAR2008项目的两景升轨及两景降轨E-SAR P波段全极化SAR数据进行试验,并采用3组反演策略进行比较分析。结果表明,三层植被模型能够更好地描述植被散射过程;同时,新方法有效降低了由垂直向波数引起的系统误差,提高了树高反演精度。
[Abstract]:The acquisition of forest parameters can not only estimate the surface biomass and understory topography, but also contribute to the study of the global carbon cycle and the analysis of global climate change. Polarimetric interferometry (SAR) inversion algorithm for vegetation parameters is generally based on a two-layer random terrane model (RVoG),. However, when the actual vegetation has a canopy, trunks and surface layers, the accuracy of vegetation parameters inversion will become worse. Because the data of airborne SAR system differ greatly in the near distance and long distance vertical wavenumber, there is a systematic error caused by the experimental results. Aiming at these two problems, this paper presents a method for inversion of vegetation parameters of polarimetric interferometric SAR model. In this method, the RVoG model of three-layer vegetation is used to correct the scattering process of microwave in penetrating vegetation, and then the systematic error is weakened by fusion of ascending and descending orbit data. The inversion algorithm of nonlinear iterative adjustment is used to invert vegetation height. In order to verify the effectiveness of this method, the two-shot ascending orbit and two-view descent orbit E-SAR P-band fully polarized SAR data from BioSAR2008 project provided by DLR are used to test, and three sets of inversion strategies are used for comparison and analysis. The results show that the three-layer vegetation model can better describe the vegetation scattering process and the new method can effectively reduce the systematic error caused by vertical wave number and improve the precision of tree height inversion.
【作者单位】：中南大学地球科学与信息物理学院;中南大学有色金属成矿预测教育部重点实验室;
【基金】：国家自然科学基金(41531068;41371335;41671356) 湖南省自然科学基金(2016JJ2141) 湖南省重点研发计划(2016SK2003) 欧空局数据合作计划(14655) 中南大学研究生自主探索创新项目(2017zzts549)~~
【分类号】：P237

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