Estimation of Radar Backscattering Coefficient of Soil Surface with Moisture Content at Microwave Frequencies

نویسنده

  • V. K. Gupta
چکیده

Co-plarized of radar backscattering coefficient 0 hh σ and 0 vv σ are estimated for soil surface using a standard theortical model IEM (Integrtion Eequation Model). The surface parameters for model are , dielectric constant and roughness, are determined by experimental technique. The real and imaginary parts ( ε' and ε") of dielectric constant of soil determine by wave guide cell method at a single microwave frequency 9.78 GHz and at temperuture33.5C. The ε' and ε" of artificially moistened soil with conductivity water, are determined at different levels of moistness varying from 0.0% to 21.0% (gravimetrically) . Roughness of soil surface, RMS (root mean squre) height and corelation length are measured by a pin profilometer. It was observed that both 0 hh σ and 0 vv σ have the respective corelation with soil moisture content. The angular variation of 0 hh σ and 0 vv σ is according to Fresnel reflectivity of two types of polarizations. Introduction Microwave remote sensing is highly useful, as it provides observation of the earth’s surface, regardless of day/night and the atmospheric conditions, propagation through ionosphere with minimum loss. Radar is an active microwave remote sensing system. The system illuminates the terrain with electromagnetic energy (microwave), detects the scattered energy returning from the terrain (called radar return) and then records it as an image. Intensity of radar return, for both aircraft and satellite-based systems, depends upon radar system properties and terrain properties. The microwave signatures of the object are governed by the sensor parameters (frequency, polarization, incidence angle) and the physical (surface roughness, feature and 510 V.K. Gupta and Dr. R.A. Jangid orientation) and electrical (dielectric constant) property of the target. Radar backscattering coefficient ( 0 σ ) is the basic observable parameter at the sensor in active microwave remote sensing. The backscattering coefficient 0 σ , which is a unit less quantity representing the radar cross-section (m) of a given pixel on the ground per unit physical area of that pixel (m) may exhibit a wide dynamic range, and therefore is often presented in decibels. The back scattering coefficient ( 0 σ ) of a non periodic random surface can be expressed as the product of two functions [1] as given by the following equation (1): ) }, { ( ). ( 0 θ ξ ρ ε σ f f = (1) where ) (ε f is the dielectric function and ) }, { ( θ ξ ρ f is the roughness function. Surface roughness characteristics generally have been described in terms of the three important parameters namely: (i) RMS height or standard deviation of height (σ) describes the variation in surface elevation. It is an estimation of the variance of the vertical dimension in the test surface. (ii) Correlation length (l) describes the horizontal distance over which the surface profile is auto correlated with a value larger than 1/e (≅ 0.368). (iii) Auto correlation function (ρ) describe shape and degree of roughness of surface. Further, backscattering coefficient ( 0 σ ) depends on sensor properties such as frequency, polarization of microwaves and the angle of observation.Surface scattering methods usually relate geometric and dielectric properties to a bare soil surface to the radar backscatter. Three different modeling approaches have been presented in the literature for the calculation of surface radar backscattering coefficients ( 0 σ ) namely: (i) Theoretical (ii) Semi-empirical and (iii) Empirical. Theoretical backscattering model is derived from the application of the theory of electromagnetic wave scattering from a randomly rough conducting surface. Theoretical backscattering model provide site independent relationships, that are valid for different sensor configurations and the effects of different surface parameters on backscattering are taken into account. Hence, in spite of their complexity, only theoretical models can yield a significant understanding of the interaction between the electromagnetic waves and the earth's surface. Thus, the theoretical backscattering models are preferable than empirical and semi-empirical backscattering models, The most frequently used theoretical surface scattering methods are originated from the Kirchhoff approaches [2] and the Small Perturbation Method [3]. These models have different validity restrictions for the frequency and roughness ranges concerned. Hence the lack of consistency and universality in their applications is observed. So Kirchhoff model (KM) and Small Perturbation Model (SPM) have limited domains of applicability. Using the Integral Equation Model (IEM) for the surface scattering coefficient circumvents the limitations [4]. Integral equation model (IEM) For bare soil studies, the IEM has become the most widely used scattering model [4]. The integral equation model (IEM) was developed by Fung et al. [5] (1992), and is shown to unite the KM and SPM, hence making it applicable to a wider range of Estimation of Radar Backscattering Coefficient 511 roughness conditions and frequencies. The validity range [5] of the single scattering approximation of the IEM was defined as koσ < 3, where σ is the RMS surface height 0 k is free space wave number . In its complete version, the model describes the backscattering behavior of a random rough bare surface without any limitation on the roughness scale or frequency range, and accounts for both single and multiple surfaces scattering of a rough surface. Because of its complexity, it is not practical to use the complete version of the IEM and in applications approximate solutions are usually considered. The IEM is a backscattering model for scattering from a randomly rough dielectric surface that is based on an approximate solution of a pair of integral equations for the tangential surface fields. The theoretical derivation of the IEM starts from the Stratton-Chu integral [6] which describes the scattered electric field ES observed at the sensor in terms of the tangential electric and magnetic fields at the soil surface. Because the Stratton-Chu integral is complex, some approximations are described by Fung [7] has made it simpler, in order to obtain an analytical solution. The IEM [5] used for the backscattering coefficient determinationis given by the equations ( 2 to 6) as under: σ σ σ pq zo n pq n n xo k k I w k o

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تاریخ انتشار 2010