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Pol-InSAR for Forest Biomass Estimation with the Transformation of the Polarization Basis

Abstract : An improved method that uses polarimetric and Pol-InSAR information at the L-band and P-band was proposed in this study for estimating forest biomass. In the first phase, various polarimetric and polarimetric interferometry indicators were extracted via transformation of the polarization basis. In the second phase, the particle swarm optimization method is applied to identify optimal parameter values for biomass estimation. According to the results, the correlations between the polarimetric indicators and the biomass were stronger at the P-band compared to the L-band. Polarimetric indicators that involve HV and HH–VV show the maximum correlation with biomass prior to optimization. It is demonstrated that changing the polarization basis can significantly improve the correlations of estimators with the biomass, especially at the P-band. The globally optimal estimators involve the same scattering mechanisms (volume and double-bounce scattering), and the optimal polarization bases differ slightly among most of the cases, due to the adaptation to the forest natural geometry and/or the acquisition configuration. Regarding Pol-InSAR, several tree height retrieval estimators that are based on various assumptions have been analyzed under multiple polarization basis rotations. According to the results, the RVoG phase method, which represents the forest as a low-extinction structured volume, yielded the best accuracy, with R = 0.73 and RMSE = 4.30 m. The identification of the optimum polarization indicators via binary PSO could improve the biomass estimation accuracy by 2% and 6% at the P-band and L-band, respectively. It is demonstrated that such an approach can be employed to accurately estimate biomass via extrapolation of in situ measurements over an entire region.
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https://hal-normandie-univ.archives-ouvertes.fr/hal-02317819
Contributor : Pierre Weill <>
Submitted on : Wednesday, October 16, 2019 - 1:29:58 PM
Last modification on : Monday, April 27, 2020 - 4:26:30 PM

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Samira Hosseini, Hamid Ebadi, Yasser Maghsoudi, Franck Garestier. Pol-InSAR for Forest Biomass Estimation with the Transformation of the Polarization Basis. Journal of the Indian Society of Remote Sensing, 2019, 47 (7), pp.1097-1109. ⟨10.1007/s12524-019-00972-0⟩. ⟨hal-02317819⟩

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