Speaker
Description
Electromagnetic scattering mechanisms in agricultural scenarios, i.e. in dependency of dielectric and geometric soil and plant parameters, are highly complex. Towards an inversion of such parameters from multi-parametric SAR measurements, it is therefore of interest to separate the scattering mechanisms occurring on the ground, i.e. surface (soil) and dihedral (soil-trunk interactions) scattering, from the volume scattering in the vegetation layer above. In this respect, the observation space provided by polarimetric SAR measurements is limited. Therefore, model-based decomposition techniques commonly assume that either surface or dihedral scattering can be neglected. Additionally, it is not necessarily given, that the scattering mechanisms associated to the ground (surface or dihedral) are actually located at the ground height.
By utilizing one or multiple spatial baselines, the variation of the interferometric coherence with polarization allows separating scattering mechanisms along height and a two-layer model – ground plus vegetation – can be employed for ground and volume separation. [1,2]. Knowing the interferometric coherences associated to ground and volume scattering then enables to estimate the ground and volume polarimetric covariance matrices [2,3]. It can be assumed that the ground height is a priori known, e.g. from an external digital terrain model, thus fixing the interferometric ground coherence. However, the estimation of the interferometric volume coherence is intrinsically ambiguous and is subject to regularization constraints, independently of the number of available baselines [3,4,5]. As a direct consequence, also the estimation of the polarimetric ground and volume covariance matrices is ambiguous and this clearly impacts their physical interpretation and any parameter inversion attempt.
This work intends to give an overview of the aforementioned problematic using airborne SAR data acquired by DLR’s F-SAR in the frame of the CROPEX 2014 campaign. Polarimetric, multi-baseline SAR data at X-, C- and L-band are available as well as simultaneously collected in-situ measurements of soil and plant parameters on eight different dates between May and August [5]. This unique data set allows investigating the impact of different regularization constraints on the ground and volume scattering separation as a function of frequency and number of baselines on one hand and crop type and phenological stage on the other hand.
[1] S. R. Cloude, and K. P. Papathanassiou, “Three-Stage Inversion Process for Polarimetric SAR Interferometry”, Proc. Inst. Elect. Eng. - Radar, Sonar Navig., vol 150, no. 11, pp. 2352-2363, Jun. 2003.
[2] S. Tebaldini, “Algebraic Synthesis of Forest Scenarios from Multibaseline PolInSAR Data”, IEEE Trans. Geosci. Remote Sens., vol. 47, no. 12, pp. 4132-4142, Dec. 2009
[3] M. Pardini, and K. Papathanassiou, “On the Estimation of Ground and Volume Polarimetric Covariances in Forest Scenarios with SAR Tomography,” IEEE Geosci. Remote Sens. Lett., vol. 14, no. 10, pp. 1860-1864, Oct. 2017.
[4] A. Alonso-Gonzalez, and K. P. Papathanassiou, "Multibaseline Two Layer Model PolInSAR Ground and Volume Separation," Proc. of EUSAR 2018, vol. 12, Aachen, Germany, 2018.
[5] H. Joerg, M. Pardini, I. Hajnsek, and K. P. Papathanassiou, “3-D Scattering Characterization of Agricultural Crops at C-Band Using SAR Tomography”, IEEE Trans. Geosci. Remote Sens., vol. 56, no. 7, pp. 3976-3989, 2018.
