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Remote Sens. 2017, 9(6), 580; doi:10.3390/rs9060580

In-Situ Measurement of Soil Permittivity at Various Depths for the Calibration and Validation of Low-Frequency SAR Soil Moisture Models by Using GPR

1
School of Science and Engineering, Tokyo Denki University, Ishizaka, Hatoyama-machi, Hiki-gun, Saitama 350-0394, Japan
2
Center for North East Asian Studies, Tohoku University, 41 Kawauchi, Sendai, Miyagi 850-8576, Japan
3
Institute of Electromagnetics and Acoustics, Department of Electronic Science, Xiamen University, Xiamen 361005, China
4
Japan Aerospace Exploration Agency, Earth Observation Research Center, 2-1-1 Sengen, Tsukuba, Ibaraki 305-8505, Japan
5
School of Geology and Mining Engineering, Mongolian University of Science and Technology, 8th Khoroo, Baga Toiruu, Ulaanbaatar-46/520, Mongolia
*
Author to whom correspondence should be addressed.
Academic Editors: Bruce Chapman, Paul Siqueira and Prasad S. Thenkabail
Received: 18 April 2017 / Revised: 27 May 2017 / Accepted: 8 June 2017 / Published: 9 June 2017
(This article belongs to the Special Issue Calibration and Validation of Synthetic Aperture Radar)
View Full-Text   |   Download PDF [4037 KB, uploaded 12 June 2017]   |  

Abstract

At radar frequencies below 2 GHz, the mismatch between the 5 to 15 cm sensing depth of classical time domain reflectometry (TDR) probe soil moisture measurements and the radar penetration depth can easily lead to unreliable in situ data. Accurate quantitative measurements of soil water contents at various depths by classical methods are cumbersome and usually highly invasive. We propose an improved method for the estimation of vertical soil moisture profiles from multi-offset ground penetrating radar (GPR) data. A semi-automated data acquisition technique allows for very fast and robust measurements in the field. Advanced common mid-point (CMP) processing is applied to obtain quantitative estimates of the permittivity and depth of the reflecting soil layers. The method is validated against TDR measurements using data acquired in different environments. Depth and soil moisture contents of the reflecting layers were estimated with root mean square errors (RMSE) on the order of 5 cm and 1.9 Vol.-%, respectively. Application of the proposed technique for the validation of synthetic aperture radar (SAR) soil moisture estimates is demonstrated based on a case study using airborne L-band data and ground-based P-band data. For the L-band case we found good agreement between the near-surface GPR estimates and extended integral equation model (I2EM) based SAR retrievals, comparable to those obtained by TDR. At the P-band, the GPR based method significantly outperformed the TDR method when using soil moisture estimates at depths below 30 cm. View Full-Text
Keywords: BIOMASS; CMP; L-band; P-band; permittivity; Pi-SAR-L2; soil moisture; vadose zone BIOMASS; CMP; L-band; P-band; permittivity; Pi-SAR-L2; soil moisture; vadose zone
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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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MDPI and ACS Style

Koyama, C.N.; Liu, H.; Takahashi, K.; Shimada, M.; Watanabe, M.; Khuut, T.; Sato, M. In-Situ Measurement of Soil Permittivity at Various Depths for the Calibration and Validation of Low-Frequency SAR Soil Moisture Models by Using GPR. Remote Sens. 2017, 9, 580.

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