Soil moisture is an essential component of the three-phase system (solid, water, and gas) and is a driver of many soil physical, chemical, and biological processes. Plant growth and soil microbial activity require soil water content, which influences the accumulation and cycling of soil organic carbon. Various methods, such as in situ measurements, terrestrial surface modelling, and remote sensing, can be used to obtain a soil moisture dataset. This research introduces multiple methods of measuring soil moisture. Before the SMAP and SMOS missions launched, in situ measurements were the standard methods for calculating and extracting soil moisture from the soil surface. Only small areas can be used for these methods. In recent decades, remote sensing techniques have become the most accurate and widely used method for computing and mapping soil water content globally. Combining in situ and remote sensing approaches is of interest to most researchers nowadays. In the future, high-quality digital instruments will be produced, and the assimilation of satellite measurements will yield more accurate and precise results. By combining future information with models and observational tools, the accuracy of soil moisture estimation will improve. New technologies such as UAVs, remote-sensing missions such as NISAR, and IoT-based sensor networks can generate higher-resolution soil moisture data and support more precise management. These developments expand the scope for analysis in soil moisture studies and facilitate enhanced access to real-time information for researchers, farmers, scientists, and policymakers.

Soil moisture measurements: a review

Mancini, Marco
2026-01-01

Abstract

Soil moisture is an essential component of the three-phase system (solid, water, and gas) and is a driver of many soil physical, chemical, and biological processes. Plant growth and soil microbial activity require soil water content, which influences the accumulation and cycling of soil organic carbon. Various methods, such as in situ measurements, terrestrial surface modelling, and remote sensing, can be used to obtain a soil moisture dataset. This research introduces multiple methods of measuring soil moisture. Before the SMAP and SMOS missions launched, in situ measurements were the standard methods for calculating and extracting soil moisture from the soil surface. Only small areas can be used for these methods. In recent decades, remote sensing techniques have become the most accurate and widely used method for computing and mapping soil water content globally. Combining in situ and remote sensing approaches is of interest to most researchers nowadays. In the future, high-quality digital instruments will be produced, and the assimilation of satellite measurements will yield more accurate and precise results. By combining future information with models and observational tools, the accuracy of soil moisture estimation will improve. New technologies such as UAVs, remote-sensing missions such as NISAR, and IoT-based sensor networks can generate higher-resolution soil moisture data and support more precise management. These developments expand the scope for analysis in soil moisture studies and facilitate enhanced access to real-time information for researchers, farmers, scientists, and policymakers.
2026
Data Assimilation
Ground-based measurements
Machine learning
Remote sensing
Soil moisture modelling
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1311405
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