Title :
Computation of Radar Scattering From Heterogeneous Rough Soil Using the Finite-Element Method
Author :
Khankhoje, Uday K. ; van Zyl, J.J. ; Cwik, T.A.
Author_Institution :
Nat. Aeronaut. & Space Adm. Jet Propulsion Lab., California Inst. of Technol., Pasadena, CA, USA
Abstract :
A 2-D vector-element-based finite-element method (FEM) is used to calculate the radar backscatter from 1-D bare rough soil surfaces which can have an underlying heterogeneous substrate. Monte Carlo simulation results are presented for scattering at L-band (λ = 0.24 m). For homogeneous soils with rough surfaces, the results of FEM are compared with the predictions of the small perturbation method. In the case of heterogeneous substrates, soil moisture (and, hence, soil permittivity) is assumed to vary as a function of depth. In this case, the results of FEM are compared with those of the transfer matrix method for flat soil surfaces. In both cases, a good agreement is found. For homogeneous rough soils, it is found that polarimetric radar backscatter and copolarized phase difference have a nonlinear relationship with soil moisture. Finally, it is found that the nature of the soil moisture variation in the top few centimeters of the soil has a strong influence on the backscatter and, hence, on the inferred soil moisture content.
Keywords :
Monte Carlo methods; backscatter; electromagnetic wave scattering; finite element analysis; hydrological techniques; moisture; permittivity; radiowave propagation; remote sensing by radar; soil; 1D bare rough soil surfaces; 2D vector element based FEM; L-band scattering; Monte Carlo simulation; finite element method; heterogeneous rough soil radar scattering; heterogeneous substrates; radar backscatter; small perturbation method; soil moisture; soil permittivity; transfer matrix method comparison; wavelength 0.24 m; Backscatter; Finite element methods; Rough surfaces; Soil moisture; Surface roughness; Surface waves; Electromagnetic scattering by rough surfaces; Monte Carlo simulations; finite-element methods (FEMs); subsurface sensing;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2012.2225431