Articles | Volume 13, issue 1
https://doi.org/10.5194/gi-13-9-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gi-13-9-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Jan 2024
Research article |
| 16 Jan 2024
| 16 Jan 2024
Testing a novel sensor design to jointly measure cosmic-ray neutrons, muons and gamma rays for non-invasive soil moisture estimation
Stefano Gianessi
Department of Agricultural and Food Science, University of Bologna, 40127 Bologna, Italy
now at: FINAPP s.r.l., Montegrotto Terme, 35036 Padova, Italy
Matteo Polo
FINAPP s.r.l., Montegrotto Terme, 35036 Padova, Italy
now at: Department of Industrial Engineering, University of Trento, Trento, Italy
Luca Stevanato
FINAPP s.r.l., Montegrotto Terme, 35036 Padova, Italy
Marcello Lunardon
FINAPP s.r.l., Montegrotto Terme, 35036 Padova, Italy
Department of Physics and Astronomy, University of Padova, 35100 Padova, Italy
Till Francke
Institute of Environmental Science and Geography, University of Potsdam, Potsdam, Germany
Sascha E. Oswald
Institute of Environmental Science and Geography, University of Potsdam, Potsdam, Germany
Hami Said Ahmed
Soil and Water Management and Crop Nutrition Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture Vienna, Vienna, Austria
Arsenio Toloza
Soil and Water Management and Crop Nutrition Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture Vienna, Vienna, Austria
Georg Weltin
Soil and Water Management and Crop Nutrition Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture Vienna, Vienna, Austria
Gerd Dercon
Soil and Water Management and Crop Nutrition Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture Vienna, Vienna, Austria
Emil Fulajtar
Soil and Water Management and Crop Nutrition Section Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture Vienna, Vienna, Austria
Lee Heng
Soil and Water Management and Crop Nutrition Section Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture Vienna, Vienna, Austria
Department of Agricultural and Food Science, University of Bologna, 40127 Bologna, Italy
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Cited
13 citations as recorded by crossref.
- COSMIC-SWAMP: IoT Processing of Cosmic Ray Soil Moisture Sensors P. Stowell et al.
- Accuracies and costs of prediction and mapping soil properties using proximal sensors: A systematic review C. Lozano-Fondón et al.
- Cosmic-Ray Neutron Sensing as a multi-purpose technology in eLTER platforms E. Gazzola et al.
- Integrating Proximal Gamma Ray and Cosmic Ray Neutron Sensors to Assess Soil Moisture Dynamics in an Agricultural Field in Spain L. Gaspar et al.
- Field Testing of Gamma-Spectroscopy Method for Soil Water Content Estimation in an Agricultural Field S. Becker et al.
- Simulating the attenuation of in situ 40K gamma rays to monitor soil properties R. McTaggart
- Assembled Hexagonal Boron Nitride Flakes Arrays for Lateral Neutron Detectors J. Li et al.
- Comparison of Soil Water Content from SCATSAR-SWI and Cosmic Ray Neutron Sensing at Four Agricultural Sites in Northern Italy: Insights from Spatial Variability and Representativeness S. Emamalizadeh et al.
- The Potsdam Soil Moisture Observatory: high-coverage reference observations at kilometer scale P. Grosse et al.
- Virtual Joint Field Campaign: a framework of synthetic landscapes to assess multiscale measurement methods of water storage T. Francke et al.
- The PRISMA-36 array for studying variations of the thermal neutron flux M. Amelchakov et al.
- Airborne radiometric data: in search of the lost peatlands, Anglesey, North Wales D. Beamish & J. White
- Soil moisture measurements by Cosmic-Ray neutron sensing: A critical review M. Köhli
13 citations as recorded by crossref.
- COSMIC-SWAMP: IoT Processing of Cosmic Ray Soil Moisture Sensors P. Stowell et al.
- Accuracies and costs of prediction and mapping soil properties using proximal sensors: A systematic review C. Lozano-Fondón et al.
- Cosmic-Ray Neutron Sensing as a multi-purpose technology in eLTER platforms E. Gazzola et al.
- Integrating Proximal Gamma Ray and Cosmic Ray Neutron Sensors to Assess Soil Moisture Dynamics in an Agricultural Field in Spain L. Gaspar et al.
- Field Testing of Gamma-Spectroscopy Method for Soil Water Content Estimation in an Agricultural Field S. Becker et al.
- Simulating the attenuation of in situ 40K gamma rays to monitor soil properties R. McTaggart
- Assembled Hexagonal Boron Nitride Flakes Arrays for Lateral Neutron Detectors J. Li et al.
- Comparison of Soil Water Content from SCATSAR-SWI and Cosmic Ray Neutron Sensing at Four Agricultural Sites in Northern Italy: Insights from Spatial Variability and Representativeness S. Emamalizadeh et al.
- The Potsdam Soil Moisture Observatory: high-coverage reference observations at kilometer scale P. Grosse et al.
- Virtual Joint Field Campaign: a framework of synthetic landscapes to assess multiscale measurement methods of water storage T. Francke et al.
- The PRISMA-36 array for studying variations of the thermal neutron flux M. Amelchakov et al.
- Airborne radiometric data: in search of the lost peatlands, Anglesey, North Wales D. Beamish & J. White
- Soil moisture measurements by Cosmic-Ray neutron sensing: A critical review M. Köhli
Saved (final revised paper)
Latest update: 20 May 2026
Short summary
Soil moisture monitoring is important for many applications, from improving weather prediction to supporting agriculture practices. Our capability to measure this variable is still, however, limited. In this study, we show the tests conducted on a new soil moisture sensor at several locations. The results show that the new sensor is a valid and compact alternative to more conventional, non-invasive soil moisture sensors that can pave the way for a wide range of applications.
Soil moisture monitoring is important for many applications, from improving weather prediction...
