A new polarimetric change detector in radar imagery

Marino, Armando; Cloude, Shane R. and Lopez-Sanchez, Juan M. (2013). A new polarimetric change detector in radar imagery. IEEE Transactions on Geoscience and Remote Sensing, 51(5) 2986 -3000.

DOI: https://doi.org/10.1109/TGRS.2012.2211883


In modern society, the anthropogenic influences on ecosystems are central points to understand the evolution of our planet. A polarimetric SAR (synthetic aperture radar) may have a significant contribution in tackling problems concerning land use change, since such data are available with any-weather conditions. Additionally, the discrimination capability can be enhanced by the polarimetric analysis.

Recently, an algorithm able to identify targets scattering an electromagnetic wave with any degree of polarization has been developed, which makes use of a vector rearrangement of the elements of the coherency matrix. In the present work, this target detector is modified in order to perform change
detection between two polarimetric acquisitions, for land use monitoring purposes. Regarding the selection of the detector parameters, a physical rationale is followed, developing a new parameterization of the algebraic space where the detector is defined. As it will be illustrated in the following, this space is 6 dimensional complex with restrictions due to the physical feasibility of the vectors. Specifically, a link between the detector parameters and the angle differences of the eigenvector model is obtained. Moreover, a dual polarimetric version of the change detector is developed, in case that quad-polarimetric data are not available.

With the purpose of testing the methodology, a variety of datasets were exploited: quad-polarimetric airborne data
at L-band (E-SAR), quad-polarimetric satellite data at C-band (Radarsat-2), and dual-polarimetric satellite data at X-band (TerraSAR-X). The algorithm results show agreement with the available information about land changes. Moreover, a comparison with a known change detector based on the maximum likelihood ratio is presented, providing improvements in some conditions. The two methodologies differ in the analysis of the total amplitude of the backscattering, where the proposed algorithm does not take this into consideration.

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