Soil permittivity measurement using interferometry method with mass-market grade GNSS devices

Abstract Accurate soil moisture monitoring is essential for agriculture and disaster prevention. However, existing methods often rely on expensive sensors or are limited by satellite coverage. In this study, we propose a low-cost and practical method for estimating soil permittivity using signal-to-noise ratio (SNR) data in the National Marine Electronics Association (NMEA) format from low-cost mass-market GNSS receivers. We developed a theoretical model that links SNR amplitude to soil permittivity via the Fresnel reflection coefficient and validated it through field experiments at multiple antenna heights. By interpolating the elevation angle data and analyzing the SNR amplitude at elevation angles of 20°or greater, we minimized the effects of nonlinearity and achieved a strong correlation with independently measured soil permittivity. Our results demonstrate that lower antenna heights enhance accuracy and reduce variability. This method enables calibration at a single location and permits accurate permittivity estimation at other sites using only low-cost mass-market GNSS devices. The approach offers a scalable and affordable solution for soil moisture estimation across various soil textures, thereby enhancing the applicability of GNSS-IR in precision agriculture and environmental monitoring.

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Publication Details

Journal
GPS Solutions
Published
2025-11-10
DOI
https://doi.org/10.1007/s10291-025-01981-y
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
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article

Soil permittivity measurement using interferometry method with mass-market grade GNSS devices

Kosuke Noborio, Yuichi Maruo, Daiki Kobayashi, Shinsuke Aoki et al.
GPS Solutions
Soil Moisture and Remote Sensing
article

Soil permittivity measurement using interferometry method with mass-market grade GNSS devices

Kosuke Noborio, Yuichi Maruo, Daiki Kobayashi, Shinsuke Aoki, Shunsuke Kodaira
article en

Abstract

Abstract Accurate soil moisture monitoring is essential for agriculture and disaster prevention. However, existing methods often rely on expensive sensors or are limited by satellite coverage. In this study, we propose a low-cost and practical method for estimating soil permittivity using signal-to-noise ratio (SNR) data in the National Marine Electronics Association (NMEA) format from low-cost mass-market GNSS receivers. We developed a theoretical model that links SNR amplitude to soil permittivity via the Fresnel reflection coefficient and validated it through field experiments at multiple antenna heights. By interpolating the elevation angle data and analyzing the SNR amplitude at elevation angles of 20°or greater, we minimized the effects of nonlinearity and achieved a strong correlation with independently measured soil permittivity. Our results demonstrate that lower antenna heights enhance accuracy and reduce variability. This method enables calibration at a single location and permits accurate permittivity estimation at other sites using only low-cost mass-market GNSS devices. The approach offers a scalable and affordable solution for soil moisture estimation across various soil textures, thereby enhancing the applicability of GNSS-IR in precision agriculture and environmental monitoring.

GPS SolutionsVol. 30(1)
Meiji University (JP), Kagawa University (JP), NTT (Japan) (JP)
Openalex Percentile: Top 69%
Soil Moisture and Remote Sensing
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