Abstract
The aim of this paper is to analyze the potential of X-band SAR measurements (COSMO-SkyMed and TerraSAR-X) made over bare soils for the estimation of soil moisture and surface geometry parameters at a semi-arid site in Tunisia (North Africa). Radar signals acquired with different configurations (HH and VV polarizations, incidence angles of 26° and 36°) are statistically compared with ground measurements (soil moisture and roughness parameters). The radar measurements are found to be highly sensitive to the various soil parameters of interest. A linear relationship is determined for the radar signals as a function of volumetric soil moisture, and a logarithmic correlation is observed between the radar signals and three surface roughness parameters: the root mean square height (Hrms), the parameter Zs = Hrms2/l (where l is the correlation length) and the parameter Zg = Hrms × (Hrms/l)α (where α is the power of the surface height correlation function). The highest dynamic sensitivity is observed for Zg at high incidence angles. Finally, the performance of different physical and semi-empirical backscattering models (IEM, Baghdadi-calibrated IEM and Dubois models) is compared with SAR measurements. The results provide an indication of the limits of validity of the IEM and Dubois models, for various radar configurations and roughness conditions. Considerable improvements in the IEM model performance are observed using the Baghdadi-calibrated version of this model.
Highlights
Physical soil properties such as roughness and moisture need to be estimated in various scientific applications, such as hydrological and erosion modeling, agriculture, and the management of sustainable natural resources [1,2]
The most frequently used models are the Integral Equation Model IEM of Fung et al [13,14] and the Advanced Integrated Equation Model (AIEM) [15,16], which are applicable to a large range of soil roughness conditions, as well as semi-empirical models such those of Oh [17] and Dubois [18], which provide simple analytical relationships between the backscattered radar signal and physical soil parameters
The IEM’s domain of applicability covers a wide range of roughness values [13], which can be approximated by k × Hrms < 3, corresponding to Hrms < 1.5 cm in the X-Band, where k is the wavenumber of the radar signal
Summary
Physical soil properties such as roughness and moisture need to be estimated in various scientific applications, such as hydrological and erosion modeling, agriculture, and the management of sustainable natural resources [1,2]. The parameters characterizing agricultural soils have very high spatial and temporal variabilities, and conventional spot soil moisture and surface roughness measurements do not provide an adequate description of this variability. The backscattered radar signal is very sensitive to dielectric (soil moisture) and geometric (roughness) soil surface properties [10,11,12]. The most frequently used models are the Integral Equation Model IEM of Fung et al [13,14] and the Advanced Integrated Equation Model (AIEM) [15,16], which are applicable to a large range of soil roughness conditions, as well as semi-empirical models such those of Oh [17] and Dubois [18], which provide simple analytical relationships between the backscattered radar signal and physical soil parameters
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