Effect of salinity on the dielectric properties of geological materials: Implication for soil moisture detection by means of radar remote sensing

被引:96
作者
Lasne, Yannick [2 ]
Paillou, Philippe [2 ]
Freeman, Anthony [1 ,3 ]
Farr, Tom [3 ]
McDonald, Kyle C. [1 ,3 ]
Ruffié, Gilles [4 ]
Malézieux, Jean-Marie [5 ]
Chapman, Bruce [3 ]
Demontoux, François [4 ]
机构
[1] Observatoire Aquitain des Sciences de l'Univers
[2] Jet Propulsion Laboratory, California Institute of Technology, Pasadena
[3] Nationale Supérieure de Chimie Physique de Bordeaux, IMS-UMR5218
[4] EGIG-Bordeaux 3 Institute
来源
IEEE Transactions on Geoscience and Remote Sensing | 2008年 / 46卷 / 06期
关键词
Dielectric mixing model; Evaporites; Integral equation model (IEM); Polarimetry; Radar backscattering; Salinity; Soil moisture; Synthetic aperture radar (SAR);
D O I
10.1109/TGRS.2008.916220
中图分类号
学科分类号
摘要
We consider the exploitation of dielectric properties of saline deposits for the detection and mapping of moisture in arid regions on both Earth and Mars. We present simulated and experimental study in order to assess the effect of salinity on the complex permittivity of geological materials and, therefore, on the radar backscattering coefficient in the [1-7 GHz] frequency range. Laboratory measurements are performed on sand/sodium chloride aqueous mixtures using a vectorial network analyzer coupled to an open-ended coaxial dielectric probe. We aim at calibrating and validating semiempirical dielectric mixing models. In particular, we evaluated the dependence of the real and imaginary parts of complex permittivity on the microwave frequency, water content, and salinity. Our results confirm that if the real part is mainly affected by the moisture content, the imaginary part is more sensitive to salinity. In addition to the classic formulas of mixing models, the ionic-conductivity losses, which are due to mobile ions in the saline solution, are taken into account in order to better assess the effect of salinity on the dielectric properties of mixtures. Dielectric mixing models are then used as input parameters for the simulation of the radar backscattering coefficients by means of an analytical model: the integral equation model. Simulation results show that salinity should have a significant impact on the radar backscattering recorded in synthetic aperture radar data in terms of the magnitude of the backscattering coefficient. Moreover, our results suggest that VV polarization provides a greater sensitivity to salinity than HH polarization. © 2008 IEEE.
引用
收藏
页码:1674 / 1688
页数:14
相关论文
共 50 条
[1]  
Lasne Y., Paillou P., August-Bernex T., Ruffle G., Grandjean G., A phase signature for detecting wet subsurface structures using Polarimetrie L-band SAR, IEEE Trans. Geosci. Remote Sens, 42, 8, pp. 1683-1694, (2004)
[2]  
Bindlish R., Barros A.P., Sub-pixel variability on remotely sensed soil moisture: An inter-comparison study of SAR and ESTAR, IEEE Trans. Geosci. Remote Sens, 40, 2, pp. 326-337, (2002)
[3]  
Shi J., Wang J., Hsu A.Y., O'Neill P.E., Engman E.T., Estimation of bare surface soil moisture and surface roughness parameter using L-band SAR image data, IEEE Trans. Geosci. Remote Sens, 35, 5, pp. 1254-1266, (1997)
[4]  
Ulaby F.T., Batlivala P.P., Dobson M.C., Microwave backscatter dependence on surface roughness, soil moisture, and soil texture, Part I-Bare soil, IEEE Trans. Geosci. Electron, GE-16, 4, pp. 286-295, (1978)
[5]  
Ulaby F.T., Moore R.K., Fung A.K., Microwave Remote Sensing: Active and Passive, pp. 2017-2119, (1981)
[6]  
Fung A.K., Microwave Scattering and Emissions Models and Their Applications, (1994)
[7]  
Dubois P., van Zyl J., Engman T., Measuring soil moisture with imaging radar, IEEE Trans. Geosci. Remote Sens, 33, 4, pp. 915-926, (1995)
[8]  
Tsang L., Kong J.A., Shin R.T., Theory of Microwave Remote Sensing, (1985)
[9]  
Su Z., Troch P.A., De Troch F.P., Estimation of Surface Soil Moisture by Inversion of SAR Data, Surface Scattering From Random Rough, Bare Soils, Spatial and Temporal Soil Moisture Mapping From ERS-1/2, and JERS-1 SAR Data and Macroscale Hydrologie Modeling for Regional Climate Models (RCM), (1997)
[10]  
Li Q., Shi J., A generalized power law spectrum and its applications to the backscattering of soil surfaces based on the integral equation model, IEEE Trans. Geosci. Remote Sens, 40, 2, pp. 271-280, (2002)