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Remote Sens. 2017, 9(7), 732; https://doi.org/10.3390/rs9070732

New Approach for Calculating the Effective Dielectric Constant of the Moist Soil for Microwaves

1
Institute of Physics and Meteorology, University of Hohenheim, Stuttgart 70599, Germany
2
Center for Applied Geoscience, University of Tübingen, Tübingen 72076, Germany
3
Geography and Environmental Management, University of Waterloo, Waterloo, ON N2L 3G1, Canada
*
Author to whom correspondence should be addressed.
Received: 7 May 2017 / Revised: 9 July 2017 / Accepted: 11 July 2017 / Published: 15 July 2017
(This article belongs to the Section Remote Sensing in Geology, Geomorphology and Hydrology)
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Abstract

Microwave remote sensing techniques are used, among others, for temporally and spatially highly-resolved observations of land-surface properties, e.g., for the management of agricultural productivity and water resource, as well as to improve the performances of numerical weather prediction and climate simulations with soil moisture data. In this context, the effective dielectric constant of the soil is a key variable to quantify the land surface properties. We propose a new approach for the effective dielectric constant of the multiphase soil that is based on an arithmetic average of the dielectric constants of the land-surface components with damping. The results show, on average, better agreement with experimental data than previous approaches. Furthermore, the proposed new model overcomes the theoretical limitation of previous models in the incorporation of non-physical parameters to simulate measured data experimentally with satisfactory accuracy. For microwave remote sensing such as SMAP (Soil Moisture Active Passive), SMOS (Soil Moisture and Ocean Salinity) and AMSR-E (Advanced Microwave Scanning Radiometer for EOS), the physical-based model in our study showed a 23–35% RMSE (root-mean-square error) reduction compared to the most prevalent refractive mixing model in the prediction of the dielectric constant for the real and imaginary part, respectively. Furthermore, in radiowave bands used in portable soil sensors such as TDR (time-domain reflectometer) and GPR (ground-penetrating radar) the new dielectric mixing model reduced RMSE by up to 53% in the prediction of the dielectric constant. We found that the permittivity over the saturation point (porosity of dry soil) has a very different and varying pattern compared to that measured in the unsaturated condition. However, in our study, this pattern was mathematically derived from the same mixing rule applied for the unsaturated condition. It is expected that the new dielectric mixing model might help to improve the accuracy of flood monitoring by satellite. View Full-Text
Keywords: soil moisture; relative permittivity; dielectric constant; refractive index; passive microwave remote sensing; SMOS; SMAP; AMSR-E soil moisture; relative permittivity; dielectric constant; refractive index; passive microwave remote sensing; SMOS; SMAP; AMSR-E
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Park, C.-H.; Behrendt, A.; LeDrew, E.; Wulfmeyer, V. New Approach for Calculating the Effective Dielectric Constant of the Moist Soil for Microwaves. Remote Sens. 2017, 9, 732.

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