Radiative transfer theory for polarimetric remote sensing of pine forest at P band

C. C. HSU Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Cambridge, U.S.A.

H. C. HAN Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Cambridge, U.S.A.

R. T. SHIN Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Cambridge, U.S.A.

J. A. KONG Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Cambridge, U.S.A.

A. BEAUDOIN Centre d'Etude Spatiale des Rayonnements, CNRS-Universite Paul Sabatier, Toulouse, France

T. LE TOAN Centre d'Etude Spatiale des Rayonnements, CNRS-Universite Paul Sabatier, Toulouse, France

Abstract

In this paper, the radiative transfer “RT” theory for clustered vegetation structures is developed and used to interpret polarimetric radar backseattering measurement data from pine forest. The RT theory has been widely used to calculate radar backscattering coefficients from layered geophysical media and to interpret the measurement data. However,the conventional RT theory ignores the relative phase information associated with structured scatterers. which may play an important role in the overall scattering behaviour. To take into account the clustered structures with the RT theory, the scattering function of each cluster is calculated by incorporating the phase interference of scattered fields from each component. Subsequently, the resulting phase matrix is used in the radiative transfer equations to calculate the polarimetric backscattering coefficients from layered random media embedded with vegetation clusters.A multi-scale structure model of pine forest, which includes trunks, primary and secondary branches, is used to interpret and simulate polarimetric radar response at P band “0·44Hz”. The theoretical calculations are shown to be in good agreement with the backscattering data measured at the Landes maritime pine forest during the MAESTRO 1 Campaign.

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