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Updated: Jan 5, 2026

In Situ Soil Moisture Sensors in Undisturbed Soils
Published on: November 18, 2022
Data-Driven Calibration of Soil Moisture Sensor Considering Impacts of Temperature: A Case Study on FDR Sensors
Liping Chen1,2, Lili Zhangzhong3,4, Wengang Zheng5,6
1National Research Center of Intelligent Equipment for Agriculture, Beijing 100097, China. chenlp@nercita.org.cn.
Abstract:
Commercial soil moisture sensors have been widely applied into the measurement of soil moisture content. However, the accuracy of such sensors varies due to the employed techniques and working conditions. In this study, the temperature impact on the soil moisture sensor reading was firstly analyzed. Next, a pioneer study on the data-driven calibration of soil moisture sensor was investigated considering the impacts of temperature. Different data-driven models including the multivariate adaptive regression splines and the Gaussian process regression were applied into the development of the calibration method. To verify the efficacy of the proposed methods, tests on four commercial soil moisture sensors were conducted; these sensors belong to the frequency domain reflection (FDR) type. The numerical results demonstrate that the proposed methods can greatly improve the measurement accuracy for the investigated sensors.
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