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Physical interpretation of the sensitivity of polarisation coherence to soil surface roughness

Dr Francesco Mattia (1)and Dr Thuy Le Toan(2)

(1) Istituto di Radioastronomia (IRA-CNRS), CGS-ASI, I-71500 Matera, Italy
(2) CESBIO, 18 ave. Edouard Belin, 31401 Toulouse, France

Abstract

Surface roughness is an important geo-physical parameter required for numerous applications such as agronomy, geology, risk assessment, etc. In addition, the estimate of soil roughness may provide valuable a priori information to simplify the problem of soil moisture retrieval from SAR data.

In the past, roughness discriminators based on the ratio between soil backscatter at different polarisations (i.e. sigmaHH/ sigmaVV ) and on the correlation coefficient between HH and VV channels (i.e. rhoHHVV) have been suggested. More recently, the potential of the correlation coefficient between co-polarised channels (i.e. polarisation coherence) in an arbitrary state of polarisation has been investigated. In particular, the correlation coefficient between co-polarised channels at circular polarisation (i.e. rhoRRLL ) has been found extremely sensitive to surface roughness and weakly sensitive to soil moisture content. However, notwithstanding these observations have been confirmed by several experimental studies a complete physical understanding of the phenomenon is still missing, at least in the remote sensing community.

One of the main reason for this lack of understanding is that in general, only lowest order approximations of theoretical surface scattering models are exploited in remote sensing applications. These approximations do not include the effect of multiple reflections. They cannot therefore predict accurately the whole covariance matrix often required to synthesise roughness discriminators, such as rhoRRLL. In this respect, despite the fact that higher order approximations of theoretical surface scattering models are mathematically very complex, they are necessary to give indications to understand the phenomenon and they can provide physical guidelines to develop semi-empirical approaches.

In this context, the objective of this paper is to present a simple physical framework to interpret the sensitivity of different roughness discriminators to soil roughness. The adopted interpretation scheme is based on indications provided by 2nd order approximations of surface scattering models, such as Small Perturbation Method (SPM), Small Slope Approximation (SSA) and Kirchhoff approximation (KA).

Finally, limits and perspectives of using ASAR and the forthcoming PALSAR data to retrieve surface roughness is discussed.

 

Full paper

 

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