Electromagnetic scattering from grassland. I. A fully phase-coherent scattering model

A microwave scattering formulation is presented for grassland and other short vegetation canopies. The fact that the constituent elements of these targets can be as large as the vegetation layer make this formulation problematic. For example, a grass element may extend from the soil surface to the top of the canopy, and thus the upper portion of the element can be illuminated with far greater energy than the bottom. By modeling the long, thin elements of this type of vegetation as line dipole elements, this nonuniform illumination can be accounted for. Additionally, the stature and structure of grass plants can result in situations where the average inner-product of coherent terms are significant at lower frequencies. As a result, the backscattering coefficient cannot be modeled simply as the incoherent addition of the power from each element and scattering mechanism. To determine these coherent terms, a coherent model that considers scattered fields, and not power, is provided. This formulation is then used to provide a solution to the multiple coherent scattering terms, terms which include the correlation of the scattering between both dissimilar constituent elements and dissimilar scattering mechanisms. Finally, a major component of the grass family are cultural grasses, such as wheat and barley. This vegetation is often planted in row structures, a periodic organization that can likewise result in significant coherent scattering effects, depending on the frequency and illumination pattern. Therefore, a formulation is also provided that accounts for the unique scattering of these structures.

[1]  Thuy Le Toan,et al.  Rice crop mapping and monitoring using ERS-1 data based on experiment and modeling results , 1997, IEEE Trans. Geosci. Remote. Sens..

[2]  van Zyl,et al.  On the Importance of Polarization in Radar Scattering Problems , 1986 .

[3]  Michael Wayne Whitt Microwave scattering from periodic row-structured vegetation. , 1991 .

[4]  Fawwaz T. Ulaby,et al.  Radar response of periodic vegetation canopies , 1994 .

[5]  Leung Tsang,et al.  Backscattering enhancement and clustering effects of randomly distributed dielectric cylinders overlying a dielectric half space based on Monte-Carlo simulations , 1995 .

[6]  J. Kong,et al.  Radiative transfer theory for polarimetric remote sensing of pine forest at P band , 1994 .

[7]  Kamal Sarabandi,et al.  A scattering model for thin dielectric cylinders of arbitrary cross section and electrical length , 1996 .

[8]  Keith P. B. Thomson,et al.  Adaptation of the MIMICS backscattering model to the agricultural context-wheat and canola at L and C bands , 1994, IEEE Trans. Geosci. Remote. Sens..

[9]  Kamal Sarabandi,et al.  Microwave scattering model for grass blade structures , 1993, IEEE Trans. Geosci. Remote. Sens..

[10]  Leung Tsang,et al.  Collective scattering effects of trees generated by stochastic lindenmayer systems , 1996 .

[11]  K.A. Michalski,et al.  Electromagnetic wave theory , 1987, Proceedings of the IEEE.

[12]  Kamal Sarabandi,et al.  Horizontal Propagation Through Periodic Vegetation Canopies , 1991, [Proceedings] IGARSS'91 Remote Sensing: Global Monitoring for Earth Management.

[13]  David M. Le Vine,et al.  Microwave backscattering and emission model for grass canopies , 1994, IEEE Trans. Geosci. Remote. Sens..

[14]  S. Bakhtiari,et al.  A model for backscattering characteristics of tall prairie grass canopies at microwave frequencies , 1991 .

[15]  Kamal Sarabandi,et al.  Low-frequency scattering from cylindrical structures at oblique incidence , 1990 .

[16]  Kamal Sarabandi,et al.  A coherent scattering model for forest canopies based on Monte Carlo simulation of fractal generated trees , 1996, IGARSS '96. 1996 International Geoscience and Remote Sensing Symposium.

[17]  J. Kong,et al.  Theory of microwave remote sensing , 1985 .

[18]  IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 34. NO. 4, JULY 1996 Universal Multifractal Scaling of Synthetic , 1996 .

[19]  Thuy Le Toan,et al.  Branching model for vegetation , 1992, IEEE Trans. Geosci. Remote. Sens..