顾及地形因素的S-RVOG模型和PD相干最优算法联合反演植被高度
针对极化干涉SAR植被高度反演中RVOG 模型未考虑地形影响,且三阶段算法受到地面相位估计误差和纯体相干性估计误差影响,提出了一种植被高度反演思路,采用考虑地形因素的SGRVOG 模型作为反演模型校正地形影响,同时引入PD 相干最优算法用于改善三阶段算法中直线拟合地表相位估计和纯体相干性估计精度.为验证算法的有效性,首先采用欧空局提供的PolSARpro软件模拟了不同地形坡度水平的PolInSAR数据进行仿真试验,然后采用德国宇航局提供的EGSAR 机载全极化SAR数据进行真实植被场景测试,并进行了定性和定量分析.结果表明,本文方法对于不同坡度水平数据,均能有效改善传统RVOG 反演模型中地形...
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| Published in | 测绘学报 no. 6; pp. 686 - 693 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
中南大学地球科学与信息物理学院,湖南 长沙,410083
2015
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-1595 |
| DOI | 10.11947/j.AGCS.2015.20130731 |
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| Abstract | 针对极化干涉SAR植被高度反演中RVOG 模型未考虑地形影响,且三阶段算法受到地面相位估计误差和纯体相干性估计误差影响,提出了一种植被高度反演思路,采用考虑地形因素的SGRVOG 模型作为反演模型校正地形影响,同时引入PD 相干最优算法用于改善三阶段算法中直线拟合地表相位估计和纯体相干性估计精度.为验证算法的有效性,首先采用欧空局提供的PolSARpro软件模拟了不同地形坡度水平的PolInSAR数据进行仿真试验,然后采用德国宇航局提供的EGSAR 机载全极化SAR数据进行真实植被场景测试,并进行了定性和定量分析.结果表明,本文方法对于不同坡度水平数据,均能有效改善传统RVOG 反演模型中地形影响和三阶段算法自身误差影响,反演精度更高. |
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| AbstractList | 针对极化干涉SAR植被高度反演中RVOG 模型未考虑地形影响,且三阶段算法受到地面相位估计误差和纯体相干性估计误差影响,提出了一种植被高度反演思路,采用考虑地形因素的SGRVOG 模型作为反演模型校正地形影响,同时引入PD 相干最优算法用于改善三阶段算法中直线拟合地表相位估计和纯体相干性估计精度.为验证算法的有效性,首先采用欧空局提供的PolSARpro软件模拟了不同地形坡度水平的PolInSAR数据进行仿真试验,然后采用德国宇航局提供的EGSAR 机载全极化SAR数据进行真实植被场景测试,并进行了定性和定量分析.结果表明,本文方法对于不同坡度水平数据,均能有效改善传统RVOG 反演模型中地形影响和三阶段算法自身误差影响,反演精度更高. P237; 针对极化干涉SAR植被高度反演中RVOG模型未考虑地形影响，且三阶段算法受到地面相位估计误差和纯体相干性估计误差影响，提出了一种植被高度反演思路，采用考虑地形因素的S-RVOG模型作为反演模型校正地形影响，同时引入PD相干最优算法用于改善三阶段算法中直线拟合地表相位估计和纯体相干性估计精度。为验证算法的有效性，首先采用欧空局提供的PolSARpro软件模拟了不同地形坡度水平的PolInSAR数据进行仿真试验，然后采用德国宇航局提供的E-SAR机载全极化SAR数据进行真实植被场景测试，并进行了定性和定量分析。结果表明，本文方法对于不同坡度水平数据，均能有效改善传统RVOG反演模型中地形影响和三阶段算法自身误差影响，反演精度更高。 |
| Abstract_FL | The widely used random volume over ground (RVOG)model in forest height inversion with polarimetric SAR interferometric (Pol InSAR)technology do not consider the effect of terrain slope.Besides, the classical and widely appl ied three-stage inversion method is affected by the errors about estimation of underlying topography phase and pure volume coherence.In order to correct these two types of errors,a forest height inversion strategy is proposed.On the one hand,a slope RVOG (S-RVOG)model is adopted in this paper which incorporates the range terrain slope factor to correct the terrain distortion;on the other hand,the phase diversity (PD)coherence optimization is introduced to improve accuracy of underlying topography phase estimation in l ine fit process and pure volume coherence estimation.In order to verify efficiency of the method,a simulation experiment is carried out by using Pol InSAR data in different range slope levels simulated by PolSARpro software provided by ESA.Then,E-SAR ai rborne ful l polarization data provided by DLR are uti l ized to test real scenario.Final ly,it is conducted that some qual itative and quanti-tative analyses.The results show that for the different data in different range slope levels,the inversion method promises to correct effect due to terrain distortion in RVOG model and compensate error effect in traditional three-stage inversion method.Therefore,the proposed method provides much more accurate estimation of forest parameters. |
| Author | 解清华 汪长城 朱建军 付海强 |
| AuthorAffiliation | 中南大学地球科学与信息物理学院,湖南长沙410083 |
| AuthorAffiliation_xml | – name: 中南大学地球科学与信息物理学院,湖南 长沙,410083 |
| Author_FL | FU Haiqiang WANG Changcheng XIE Qinghua ZHU Jianjun |
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| Author_xml | – sequence: 1 fullname: 解清华 汪长城 朱建军 付海强 |
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| DocumentTitle_FL | Forest Height Inversion by Combining S-RVOG Model with Terrain Factor and PD Coherence Optimization |
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| Keywords | 三阶段算法 three-stage algorithm S-RVOG(slope random volume over ground) phase diversity coherence optimization (PD) terrain distortion forest height 植被高度 地形影响 PD 相干最优 E-SAR S-RVOG (slope random volume over ground) |
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| Snippet | 针对极化干涉SAR植被高度反演中RVOG 模型未考虑地形影响,且三阶段算法受到地面相位估计误差和纯体相干性估计误差影响,提出了一种植被高度反演思路,采用考虑地形因素的SGRVOG 模型作为反演模型校正地形影响,同时引入PD... P237;... |
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| SubjectTerms | EGSAR ground over PD相干最优 random S-RVOG（slope volume 三阶段算法 地形影响 植被高度 |
| Title | 顾及地形因素的S-RVOG模型和PD相干最优算法联合反演植被高度 |
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