Quantitative Analysis of Polarimetric Model-Based Decomposition Methods
AbstractIn this paper, we analyze the robustness of the parameter inversion provided by general polarimetric model-based decomposition methods from the perspective of a quantitative application. The general model and algorithm we have studied is the method proposed recently by Chen et al., which makes use of the complete polarimetric information and outperforms traditional decomposition methods in terms of feature extraction from land covers. Nevertheless, a quantitative analysis on the retrieved parameters from that approach suggests that further investigations are required in order to fully confirm the links between a physically-based model (i.e., approaches derived from the Freeman–Durden concept) and its outputs as intermediate products before any biophysical parameter retrieval is addressed. To this aim, we propose some modifications on the optimization algorithm employed for model inversion, including redefined boundary conditions, transformation of variables, and a different strategy for values initialization. A number of Monte Carlo simulation tests for typical scenarios are carried out and show that the parameter estimation accuracy of the proposed method is significantly increased with respect to the original implementation. Fully polarimetric airborne datasets at L-band acquired by German Aerospace Center’s (DLR’s) experimental synthetic aperture radar (E-SAR) system were also used for testing purposes. The results show different qualitative descriptions of the same cover from six different model-based methods. According to the Bragg coefficient ratio (i.e.,
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Xie, Q.; Ballester-Berman, J.D.; Lopez-Sanchez, J.M.; Zhu, J.; Wang, C. Quantitative Analysis of Polarimetric Model-Based Decomposition Methods. Remote Sens. 2016, 8, 977.
Xie Q, Ballester-Berman JD, Lopez-Sanchez JM, Zhu J, Wang C. Quantitative Analysis of Polarimetric Model-Based Decomposition Methods. Remote Sensing. 2016; 8(12):977.Chicago/Turabian Style
Xie, Qinghua; Ballester-Berman, J. D.; Lopez-Sanchez, Juan M.; Zhu, Jianjun; Wang, Changcheng. 2016. "Quantitative Analysis of Polarimetric Model-Based Decomposition Methods." Remote Sens. 8, no. 12: 977.
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