Information on rice phenological stages from Synthetic Aperture Radar
(SAR) images is of prime interest for in-season monitoring. Often, prior
in-situ measurements of phenology are not available. In such situations,
unsupervised clustering of SAR images might help in discriminating
phenological stages of a crop throughout its growing period. Among the
existing unsupervised clustering techniques using full-polarimetric (FP)
SAR images, the eigenvalue-eigenvector based roll-invariant
scattering-type parameter, and the scattering entropy parameter are
widely used in the literature. In this study, we utilize a unique target
scattering-type parameter, which jointly uses the Barakat degree of
polarization and the elements of the polarimetric coherency matrix.
Likewise, we also utilize an equivalent parameter proposed for
compact-polarimetric (CP) SAR data. These scattering-type parameters are
analogous to the Cloude-Pottier’s parameter for FP SAR data and the
ellipticity parameter for CP SAR data. Besides this, we also introduce
new clustering schemes for both FP and CP SAR data for segmenting
diverse scattering mechanisms across the phenological stages of rice. In
this study, we use the RADARSAT-2 FP and simulated CP SAR data acquired
over the Indian test site of Vijayawada under the Joint Experiment for
Crop Assessment and Monitoring (JECAM) initiative. The temporal analysis
of the scattering-type parameters and the new clustering schemes help us
to investigate detailed scattering characteristics from rice across its
phenological
stages.