Eishoeei et al. (2025) Soil moisture measurements: a review

Identification

• Journal: Computers and Electronics in Agriculture
• Year: 2025
• Date: 2025-12-26
• Authors: Edith Eishoeei, Mirhassan Miryaghoubzadeh, Mahdi Erfanian, Reza Mahboobi Esfanjani, Marco Mancini
• DOI: 10.1016/j.compag.2025.111379

Research Groups

• Natural Resources Faculty, Urmia University, Urmia, Iran.
• Electrical Engineering Faculty, Sahand University of Technology, Tabriz, Iran.
• Civil Engineering Department, Politecnico di Milano (Polimi), Milan, Italy.

Short Summary

This review evaluates the evolution of soil moisture measurement techniques, from traditional in situ methods to modern remote sensing and data assimilation. It highlights the transition toward high-resolution global mapping and the integration of emerging technologies like UAVs and IoT for improved hydrological and agricultural management.

Objective

• To provide a comprehensive synthesis of soil moisture measurement methodologies, including in situ techniques, terrestrial surface modeling, remote sensing, and the integration of these data through machine learning and data assimilation.

Study Configuration

• Spatial Scale: Multi-scale, ranging from local point-based measurements (in situ) to global coverage (satellite remote sensing).
• Temporal Scale: Review of historical standards (pre-SMAP/SMOS missions) to contemporary applications and future technological projections.

Methodology and Data

• Models used: Terrestrial surface modeling, Data Assimilation (DA) frameworks, and Machine Learning (ML) algorithms.
• Data sources: In situ ground-based measurements, satellite missions (e.g., SMAP, SMOS, and the upcoming NISAR), UAV-based observations, and IoT-based sensor networks.

Main Results

• In situ measurements remain the benchmark for local accuracy but are limited by low spatial representativeness.
• Remote sensing has become the most accurate and widely used method for global soil water content mapping, particularly following the launch of SMAP and SMOS missions.
• The integration of in situ data with remote sensing via data assimilation is identified as the most effective approach for improving the precision of hydrological and climate models.
• Future advancements are expected to rely on high-quality digital instruments, UAVs, and IoT-based networks to generate higher-resolution data for real-time management.

Contributions

• Synthesizes the transition from traditional point-based measurements to integrated global monitoring systems.
• Identifies the synergy between remote sensing and data assimilation as the current frontier for improving soil moisture estimation accuracy.
• Outlines the critical role of upcoming missions (e.g., NISAR) and digital technologies (IoT) in facilitating enhanced access to information for policymakers and scientists.

Funding

• Not explicitly mentioned in the provided text.

Citation

@article{Eishoeei2025Soil,
  author = {Eishoeei, Edith and Miryaghoubzadeh, Mirhassan and Erfanian, Mahdi and Esfanjani, Reza Mahboobi and Mancini, Marco},
  title = {Soil moisture measurements: a review},
  journal = {Computers and Electronics in Agriculture},
  year = {2025},
  doi = {10.1016/j.compag.2025.111379},
  url = {https://doi.org/10.1016/j.compag.2025.111379}
}

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