Dielectric model in the frequency range 0.05 to 15 GHz at temperatures -30°C to 25°C for the samples of organic soils and litter collected in Alaska, Yamal, and Siberian Taiga

Миронов, В. Л.; Savin, I. Yu.; Karavaysky, A. Y.

doi:10.1109/igarss.2016.7729693

Cited by 4 publications

(1 citation statement)

References 2 publications

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“…Based on this, a temperature-dependent multi-relaxation spectroscopic dielectric model (TD MRSDM) was developed by Mironov et al [18]. The TD MRSDM was applied to three kinds of soils with different organic contents and Arctic soil to test its applicability [19,20]. The thermodynamic parameters were further supplemented to obtain a complete set of parameters of multiple relaxation spectra related to temperature, and the feasibility was verified.…”

Section: Ieee Geoscience and Remote Sensing Lettersmentioning

confidence: 99%

Improvement in Modeling Soil Dielectric Properties During Freeze-Thaw Transitions

Zhao

Pan

et al. 2022

IEEE Geosci. Remote Sensing Lett.

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Soil freeze-thaw cycles have a profound impact on heat and water fluxes at the land-atmosphere interface and transport in soils. Microwave remote sensing is a widely used technique to detect near-surface soil freeze/thaw states due to significant changes in dielectric properties associated with water phase transitions in soils, where uncertainty remains. This letter proposed a new parameterization scheme for the estimation of unfrozen water content to improve the modeling of soil dielectric properties during freeze-thaw transitions. Predictions from the new model referred as Zhang-Zhao's model were compared with dielectric measurements during thawing processes of soil samples collected from Baoding (silty clay soil), Zhangjiakou (loamy sandy soil), and Zhengzhou (clay loam soil) in China. The mean biases of the predictions were 3.25 (4.44 and 2.07 for the thawed value and frozen value, respectively) and 1.54 (2.22 and 0.88 for the thawed value and frozen value, respectively) for the real part and imaginary part, respectively. The model-predicted soil complex relative permittivity was highly correlated with measurements, with correlation coefficients ranging from 0.7944 to 0.9865. The normalized root mean square errors of the predictions were 13.72% (real part) and 25.41% (imaginary part).

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Section: Ieee Geoscience and Remote Sensing Lettersmentioning

confidence: 99%