首页> 外文会议>Conference on land surface and cryosphere remote sensing III >Performance of PolSAR backscatter and PolInSAR coherence for scattering characterization of forest vegetation using TerraSAR-X data
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Performance of PolSAR backscatter and PolInSAR coherence for scattering characterization of forest vegetation using TerraSAR-X data

机译:使用Terrasa-X数据散射森林植被散射特征的Polsar反向散射和PONINAR连贯性的性能

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Airborne SAR data has been successfully used for forest height inversion, however there is limited applicability in spaceborne scenario due to high temporal decorrelation. This study investigates the potential of high resolution fully polarimetric pair of TerraSAR-X/TanDEM-X SAR data acquired over Barkot forest region of Uttarakhand state in India to analyze the backscatter and coherence and to test the height inversion algorithms. Yamaguchi decomposition was implemented onto the dataset to express total backscatter as a sum of different scattering components from a single SAR resolution cell. Coherency matrix was used to compute complex coherence for different polarization channels. Forest areas suffered from low coherence due to volume decorrelation whereas dry river bed had shown high coherence. Appropriate perpendicular baseline and hence the interferometric vertical wavenumber was selected in forest height estimation. Coherence amplitude inversion (CAI) approach overestimated the forest height and also resulted in false heights for dry river bed. This limitation was overcome by implementing three stage inversion modeling (TSI) which assumes polarization independent volume coherence and the heights in dry river bed were completely eliminated. The results were validated using ground truth data available for 49 plots, and TSI was found to be more accurate with an average accuracy of 90.15% and RMSE of 2.42 m.
机译:空中SAR数据已成功用于森林高度反演,然而由于高时的延迟序列导致的空间场景中的适用性有限。本研究调查了高分辨率的潜力全极化偏振对地区的Terrasar-X / Tandem-x SAR数据在印度的Barkot Forest地区获取了乌塔塔克手州的Barkot Forest地区,分析了反向散射和一致性并测试了高度反演算法。 yamaguchi分解在数据集上实现,以表达总反向散射作为来自单个SAR分辨率小区的不同散射组件的总和。相干矩阵用于计算不同偏振通道的复合相干性。由于批量去相关性,森林地区遭受了低相干性,而干燥的河床表现出高的相干性。适当的垂直基线,因此在森林高度估计中选择干涉垂直波数。相干幅度反转(CAI)方法高估森林高度,并导致干河床的假高度。通过实施三阶段反转建模(TSI)克服了这种限制,该阶段反转建模(TSI)假设极化独立的体积相干性,并且完全消除了干河床中的高度。使用49个地块的地面真理数据验证了结果,发现TSI更准确,平均精度为90.15%,RMSE为2.42米。

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