Pulse Brain · Growing Health Evidence Index
Tier 1 — Meta-analysis / systematic reviewPeer-reviewed

Earth Observation Data-Driven Cropland Soil Monitoring: A Review

Nikolaos Tziolas, Nikolaos Tsakiridis, Sabine Chabrillat, José Alexandre Melo Demattê, Eyal Ben‐Dor, Asa Gholizadeh, George Zalidis, Bas van Wesemael

Remote Sensing · 2021

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Summary

This systematic review synthesises 46 peer-reviewed articles on Earth Observation technology for cropland soil monitoring (2019–2021), evaluating spaceborne and aerial remote sensing approaches across multiple scales and resolutions. The authors identify four key limitation categories constraining adoption and propose best practices including artificial intelligence integration, harmonised dataset sharing, in situ sensor fusion, and improved sensor resolution. The findings support a roadmap for interdisciplinary coordination to deliver policy and economic benefits from EO-based soil monitoring.

UK applicability

The review's recommendations for EO-based soil monitoring are applicable to UK agricultural monitoring and precision farming contexts, particularly regarding policy frameworks for sustainable soil management and environmental monitoring. UK agricultural policy (e.g. Environmental Land Management schemes) may benefit from adopting harmonised EO datasets and AI-driven soil mapping where infrastructure and funding barriers—identified as key limitations—can be addressed.

Key measures

Inventory of EO data-driven soil monitoring research; classification of limitations in (i) area coverage and data sharing, (ii) bare soil detection thresholds, (iii) soil surface conditions, and (iv) infrastructure capabilities; assessment of sensor resolution, modelling approaches, and artificial intelligence techniques

Outcomes reported

The review systematized recent achievements in spaceborne and aerial Earth Observation data-driven soil monitoring across 46 peer-reviewed articles (2019–2021), identifying four categories of limitations hindering wider adoption and recommending best practices for advancement. Key outcomes include analysis of scaling, resolution, data characteristics, modelling approaches, and technological barriers in EO-based topsoil monitoring.

Theme
Measurement & metrics
Subject
Soil health assessment & monitoring
Study type
Systematic Review
Study design
Systematic review
Source type
Peer-reviewed study
Status
Published
Geography
International
System type
Arable cereals
DOI
10.3390/rs13214439
Catalogue ID
SNmov5j4tp-jifsug

Topic tags

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