Evaluation of IEM, Dubois, and Oh Radar Backscatter Models Using Airborne L-Band SAR
Evaluation of IEM, Dubois, and Oh Radar Backscatter Models Using Airborne L-Band SAR
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DOI：
10.1109/tgrs.2013.2286203
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发表时间：
2014-08
影响因子：
8.2
通讯作者：
R. Panciera;M. Tanase;K. Lowell;J. Walker
中科院分区：
文献类型：
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作者：
R. Panciera;M. Tanase;K. Lowell;J. Walker
对三种常见的表面散射模型(积分方程模型、Dubois模型和OH模型)预测的后向散射进行了评估，并与L波段全极化航空观测进行了对比。在进行现场校准之前，在三种模型中，oh模型是最准确的，对于HH和VV极化，模拟的后向散射与观测的平均误差分别为1.2分贝(误差的标准差±2.6分贝)和-0.4分贝(±2.4分贝)，而IEM和Dubois的误差较大，在VV极化时，IEM的最大误差为4.5分贝(±2分贝)。观测到后向散射误差与地表粗糙度有关，这是决定土壤表面电磁散射的另一个主要因素。因此，现有的表面粗糙度关联长度的半经验校准被用于改善建模的后向散射体与观测的背向散射体之间的失配。半经验定标的应用使得IEM的后向散射预测有了很大的改善。校准后，IEM的性能优于oh模型，HH极化和VV极化的平均后向散射误差分别为-0.3分贝(±1.1分贝)和-0.2分贝(±1.2分贝)。为了测试半经验校准的稳健性，应用了来自独立数据集的校准函数，并表明该校准函数也改善了(未校准的)IEM性能，这表明该校准过程对于全球应用是相对稳健的。
The backscatter predicted by three common surface scattering models (the Integral Equation Model (IEM), the Dubois, and the Oh models) was evaluated against fully polarized L-band airborne observations. Before any site-specific calibration, the Oh model was found to be the most accurate among the three, with mean errors between the simulated and the observed backscatter of 1.2 dB ( ±2.6 dB standard deviation of the error) and -0.4 dB ( ±2.4 dB) for HH and VV polarizations, respectively, while the IEM and Dubois presented larger errors, with a maximum of 4.5 dB ( ±2 dB) for the IEM in VV polarization. The backscatter errors were observed to be related to surface roughness, another major factor determining the electromagnetic scattering at the soil surface. An existing semiempirical calibration of the surface roughness correlation length was therefore applied to improve the mismatch between modeled and observed backscatters. The application of the semiempirical calibration led to a significant improvement of the backscatter prediction for the IEM. After calibration, the IEM outperformed the Oh model, resulting in a mean backscatter error of -0.3 dB ( ±1.1 dB) and -0.2 ( ±1.2 dB) for HH and VV polarizations, respectively. To test the robustness of the semiempirical calibration, calibration functions derived from an independent data set were applied and shown to also improve the (uncalibrated) IEM performance, suggesting that the calibration procedure is relatively robust for global application.