A land
cover classification procedure is presented utilizing the information content
of fully polarimetric SAR images. The Cameron coherent target decomposition
(CTD) is employed to characterize each pixel, using a set of canonical
scattering mechanisms in order to describe the physical properties of the
scatterer. The novelty of the proposed classification approach lies on the use
of Hidden Markov Models (HMM) to uniquely characterize each type of land cover.
The motivation to this approach is the investigation of the alternation between
scattering mechanisms from SAR pixel to pixel. Depending on the observations-scattering mechanisms and
exploiting the transitions between the scattering mechanisms we decide
upon the HMM-land cover type. The classification process is based on the
likelihood of observation sequences been
evaluated by each model. The performance of the classification approach
is assessed my means of fully polarimetric SLC SAR data from the broader area of Vancouver, Canada and was found
satisfactory, reaching a success from 87% to over 99%.
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