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Fitting a two-component scattering model to polarimetric SAR data from forests

Anthony Freeman, JPL, tony.freeman@jpl.nasa.gov (Presenting)

Two simple scattering mechanisms are fitted to polarimetric SAR observations of forests. The mechanisms are canopy scatter from a cloud of randomly oriented oblate spheroids, and a ground scatter term, which can represent double-bounce scatter from a pair of orthogonal surfaces with different dielectric constants or Bragg scatter from a moderately rough surface, seen through a layer of vertically oriented scatterers. The model is shown to describe the behavior of polarimetric backscatter from a tropical forest and two temperate forest sites, by applying it to data from NASA/JPL's AIRSAR system. Scattering contributions from the two basic scattering mechanisms are estimated for clusters of pixels in polarimetric SAR images. The solution involves the estimation of four parameters from four separate equations. This model fit approach is justified as a simplification of more complicated scattering models, which require many inputs to solve the forward scattering problem. The model is used to develop an understanding of the ground-trunk, double-bounce scattering present in the data, which is seen to vary considerably as a function of incidence angle. Results from the model fit for the ground scattering term are compared with estimates from a forward model and shown to be in good agreement. The behavior of the scattering from the ground-trunk interaction is consistent with the presence of a Brewster angle effect for the air-trunk scattering interface. If the Brewster angle is known, it is possible to directly estimate the real part of the dielectric constant of the trunks, a key variable in forward modeling of backscatter from forests. It is also shown how, with a priori knowledge of the forest height, an estimate for the attenuation coefficient of the canopy can be obtained directly from the multi-incidence angle, polarimetric observations. This attenuation coefficient is another key variable in forward models and is generally related to the canopy density.

Presentation Type:  Poster

Abstract ID: 194

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