Cavalli et al. (2026) Surface Soil Moisture from Sentinel-2 Imagery: A Systematic Review Complemented by a Case Study in Sardinia, Italy

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-09-21
• Authors: Rosa Maria Cavalli, Giuseppe Esposito, Luca Pisano, Davide Notti
• DOI: 10.3390/rs18183262

Research Groups

• University of [Name]
• National Institute of [Name]

Short Summary

This study investigates the accuracy of Surface Soil Moisture (SSM) estimates using Sentinel-2 data, highlighting the importance of reference measurement design and time-series length for reliable SSM estimation.

Objective

• Can Sentinel-2 data yield accurate Surface Soil Moisture (SSM) estimates?

Study Configuration

• Spatial Scale: Plot scale with an accuracy of approximately 5 vol%
• Temporal Scale: Three-year multi-temporal comparison

Methodology and Data

• Models used: Theia SSM products, machine-learning algorithms, optical trapezoidal models, statistical methodologies
• Data sources: Sentinel-2 bands, reference measurements acquired simultaneously

Main Results

• SSM retrieval accuracy from Sentinel-2 can be strongly modulated by vegetation status and soil moisture magnitude.
• Maximum R2 (Sentinel 2-bands against Theia SSM) increases by 0.44 where NDVI is less than 0.35, and SSM is less than 15%.
• Extending the analysis to a multi-year time series improves R2 relative to single-date results.

Contributions

• This study provides concrete guidance on image selection, reference measurement design, and time-series length for researchers seeking reliable SSM estimation from Sentinel-2 data.
• The findings highlight the importance of using well-planned approaches when utilizing Sentinel-2 imagery for SSM estimation.

Funding

• Project [Name], Program [Name], Reference Code [Code]
• Project [Name], Program [Name], Reference Code [Code]

Citation

@article{Cavalli2026Surface,
  author = {Cavalli, Rosa Maria and Esposito, Giuseppe and Pisano, Luca and Notti, Davide},
  title = {Surface Soil Moisture from Sentinel-2 Imagery: A Systematic Review Complemented by a Case Study in Sardinia, Italy},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18183262},
  url = {https://doi.org/10.3390/rs18183262}
}