Soil Carbon Remote Sensing: A Meta-Analysis and Systematic Review of Published Results from 1969–2022
Abstract
1. Introduction
2. Materials and Methods
2.1. Paper Inclusion Criteria and Definition of R2
2.2. Data Categorisation and Analysis
2.3. Other Variables and Information
3. Results
3.1. Publication Record
3.2. Platforms and Sensors
3.3. Algorithms
3.4. Organic Carbon “Types”
3.5. Performance
4. Discussion
4.1. Model Training Data (Number, Density, and Distribution of Samples)
4.2. Best Wavelengths
4.3. Best Algorithm
4.4. Effects of Spectral Resolution—Is Hyperspectral Better than Multispectral Data?
4.5. Model Bias
4.6. Bare Soil Masking
4.7. Influence of Soil MC on SOC Remote Sensing Model Performance
4.8. Influence of Soil Type
4.9. Measurement Technique for Calibration/Model Training Data
4.10. Model Accuracy Metrics
4.11. Overall Summary of Findings
5. Conclusions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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McGuirk, S.L.; Cairns, I.H. Soil Carbon Remote Sensing: A Meta-Analysis and Systematic Review of Published Results from 1969–2022. Geotechnics 2025, 5, 33. https://doi.org/10.3390/geotechnics5020033
McGuirk SL, Cairns IH. Soil Carbon Remote Sensing: A Meta-Analysis and Systematic Review of Published Results from 1969–2022. Geotechnics. 2025; 5(2):33. https://doi.org/10.3390/geotechnics5020033
Chicago/Turabian StyleMcGuirk, Savannah L., and Iver H. Cairns. 2025. "Soil Carbon Remote Sensing: A Meta-Analysis and Systematic Review of Published Results from 1969–2022" Geotechnics 5, no. 2: 33. https://doi.org/10.3390/geotechnics5020033
APA StyleMcGuirk, S. L., & Cairns, I. H. (2025). Soil Carbon Remote Sensing: A Meta-Analysis and Systematic Review of Published Results from 1969–2022. Geotechnics, 5(2), 33. https://doi.org/10.3390/geotechnics5020033