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Analysis of the Backscattering Coefficient of Salt-Affected Soils Using Modeling and RADARSAT-1 SAR Data

机译:利用建模和RADARSAT-1 SAR数据分析盐渍土的反向散射系数

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Salt significantly changes the backscattering coefficient of wet soil. This is easily observed on RADARSAT-1 synthetic aperture radar (SAR) images acquired over a salty depression located in the Egyptian desert. The aim of this paper is to use backscattering models to understand the behavior of the backscattering coefficient over salt-affected soils and to evaluate the possibility of monitoring the salt content. Simulations conducted over salt-affected soils show a lower sensitivity of these models to soil moisture compared to nonaffected soils. Besides, there is no model suitable to represent the variation of the backscattering coefficient due to changes in soil salinity. These results are discussed with regard to the magnitude of the two components of the dielectric constant (epsiv' and epsiv''). Based on a series of relationships, we propose a parametric formulation that allows us to determine the salinity acting on RADARSAT-1 SAR images without any use of backscattering models
机译:盐会显着改变湿土壤的反向散射系数。在位于埃及沙漠中一个咸洼处的RADARSAT-1合成孔径雷达(SAR)图像上很容易观察到这一点。本文的目的是使用反向散射模型来了解在受盐影响的土壤上反向散射系数的行为,并评估监测盐分含量的可能性。与未受影响的土壤相比,在受盐影响的土壤上进行的模拟表明这些模型对土壤水分的敏感性较低。此外,由于土壤盐分的变化,没有合适的模型来表示后向散射系数的变化。关于介电常数的两个分量(epsiv'和epsiv'')的大小讨论了这些结果。基于一系列关系,我们提出了一种参数公式,可以使我们确定作用于RADARSAT-1 SAR图像的盐度,而无需使用任何反向散射模型

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