Ballester-Berman et al. (2026) Estimating the Coherency Matrices of Polarised and Depolarised Components of PolSAR Data

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Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-03-30
• Authors: J. David Ballester-Berman, Qinghua Xie, Hongtao shi
• DOI: 10.3390/rs18071043

Research Groups

European Microwave Signature Laboratory (EMSL)

Short Summary

This paper introduces a novel two-component decomposition method, extending the model-free three-component (MF3C) decomposition, to separate polarised and depolarised scattering contributions in PolSAR data, demonstrating its consistency with theoretical expectations across various scenarios and sensor frequencies.

Objective

• To propose and validate a two-component decomposition method for estimating the depolarised and polarised components within a target and their corresponding coherency matrices, building upon the 3-D Barakat degree of polarisation and the MF3C decomposition.

Study Configuration

• Spatial Scale: Laboratory scale (three vegetation samples) and regional scale (boreal forest in Germany).
• Temporal Scale: Single acquisition events.

Methodology and Data

• Models used: Proposed two-component decomposition, extension of the model-free three-component (MF3C) decomposition, relies on the 3-D Barakat degree of polarisation.
• Data sources: Indoor multi-frequency datasets from the European Microwave Signature Laboratory (EMSL) over three vegetation samples; P-, L-, and C-band AIRSAR images over a boreal forest in Germany.

Main Results

• The proposed two-component decomposition method consistently outputs results aligned with theoretical expectations for depolarised and polarised scattering components across a wide range of scenarios and sensor frequencies.
• Performance analysis using eigendecomposition, copolar cross-correlation, histograms, and correlation analysis confirmed the method's consistency.

Contributions

• Introduction of a novel two-component decomposition method that extends the existing model-free three-component (MF3C) decomposition.
• Provides a physical rationale, driven by the 3-D Barakat degree of polarisation, to separate polarised and depolarised contributions in PolSAR data.
• Enables the exploitation of both model-free and model-based approaches, potentially leading to more accurate retrieval of target parameters by applying existing scattering models directly to the separated components.

Funding

Not specified in the provided text.

Citation

@article{BallesterBerman2026Estimating,
  author = {Ballester-Berman, J. David and Xie, Qinghua and shi, Hongtao},
  title = {Estimating the Coherency Matrices of Polarised and Depolarised Components of PolSAR Data},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18071043},
  url = {https://doi.org/10.3390/rs18071043}
}