Underlying Topography Estimation Over Forest Areas Using Single-Baseline InSAR Data
Underlying Topography Estimation Over Forest Areas Using Single-Baseline InSAR Data
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使用单基线 InSAR 数据对森林地区进行基础地形估计
DOI：
10.1109/tgrs.2018.2878357
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发表时间：
2019
影响因子：
8.2
通讯作者：
Xie Qing Hua
中科院分区：
文献类型：
--
作者：
Fu Hai Qiang;Zhu Jian Jun;Wang Chang Cheng;Zhao Rong;Xie Qing Hua
提出了从单基线干涉合成孔径雷达(InSAR)数据中提取林区数字高程模型(DEM)的方法。该方法的主要思想是在雷达捕获过程中发生一些与森林几何结构有关的后向散射变化。时频分析被用来通过将合成的SAR图像在傅立叶域分成多个被称为子块图像的SAR图像来恢复这些变化。然后，通过干涉测量，利用基线两端空间分离位置获得的具有相同多普勒带宽的子块图像来估计子块相干性，并将上述后向散射变化转换为子块相干性的变化。因此，可以增加InSAR观测值的数量。然后用两层植被散射模型解释子块相干性，并假定它们在复平面内遵循近线性关系。然后，基相可以通过子块相干的线性回归来估计。利用L和P波段针叶林和热带森林的E-SAR数据验证了该方法的有效性。对于针叶林DEM，该方法估计的DEM的均方根误差(RMSE)为4.39m，略低于极化直线拟合法(LF)的DEM(RMSE为4.07m)，但与HH InSAR方法相比，DEM的精度有了显著的提高。在热带条件下，本文方法和极化低频方法得到的DEM比HH InSAR方法得到的DEM更接近地面，平均地高差为0.62m。两个实验证实了用该方法提取DEM是可行的，其DEM反演性能与极化低频方法相当，并且只需要单极化InSAR数据。
In this paper, a method for digital elevation model (DEM) extraction over forest areas from single-baseline interferometric synthetic aperture radar (InSAR) data is proposed. The main idea of this method is that some backscattering variations which are linked to the geometrical structures of forest occur during the radar acquisition. The time–frequency analysis is used to retrieve these variations by dividing the synthesized SAR image into multiple SAR images in the Fourier domain called sublook images. Then, by interferometry, the sublook images characterized by the same Doppler bandwidth and acquired from spatially separated locations at either end of a baseline are used to estimate the sublook coherences and the above backscattering variations are converted into the variations of sublook coherences. As a result, the number of InSAR observations can be increased. The sublook coherences are then interpreted by the two-layer vegetation scattering model and are assumed to follow a near-linear relationship in the complex plane. The ground phase can then be estimated by linear regression of the sublook coherences. The performance of the proposed method was validated by E-SAR L- and P-band SAR data acquired over coniferous and tropical forests. For the coniferous scenario, the underlying DEM estimated by the proposed method has a root-mean-square error (RMSE) of 4.39 m, which is slightly less accurate than the DEM (with an RMSE of 4.07 m) derived by the polarimetric line-fit (LF) method, but represents a significant improvement in DEM accuracy over the HH InSAR method. For the tropical scenario, the DEMs derived by the proposed method and the polarimetric LF method are closer to the ground surface than those derived by the HH InSAR method, and their mean ground height difference is 0.62 m. The two experiments confirm that it is feasible to extract a DEM by the proposed method, which has a comparable performance in DEM inversion to the polarimetric LF method and only requires single-polarization InSAR data.