The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Prediction of Soil Organic Carbon at the European Scale by Visible and Near InfraRed Reflectance Spectroscopy
Open accessAbstract
Soil organic carbon is a key soil property related to soil fertility, aggregate stability and the exchange of CO2 with the atmosphere. Existing soil maps and inventories can rarely be used to monitor the state and evolution in soil organic carbon content due to their poor spatial resolution, lack of consistency and high updating costs. Visible and Near Infrared diffuse reflectance spectroscopy is an alternative method to provide cheap and high-density soil data. However, there are still some uncertainties on its capacity to produce reliable predictions for areas characterized by large soil diversity. Using a large-scale EU soil survey of about 20,000 samples and covering 23 countries, we assessed the performance of reflectance spectroscopy for the prediction of soil organic carbon content. The best calibrations achieved a root mean square error ranging from 4 to 15 g C kg(-1) for mineral soils and a root mean square error of 50 g C kg(-1) for organic soil materials. Model errors are shown to be related to the levels of soil organic carbon and variations in other soil properties such as sand and clay content. Although errors are ∼5 times larger than the reproducibility error of the laboratory method, reflectance spectroscopy provides unbiased predictions of the soil organic carbon content. Such estimates could be used for assessing the mean soil organic carbon content of large geographical entities or countries. This study is a first step towards providing uniform continental-scale spectroscopic estimations of soil organic carbon, meeting an increasing demand for information on the state of the soil that can be used in biogeochemical models and the monitoring of soil degradation.
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Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162
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Savitzky, A., & Golay, M. J. E. (1964) · Analytical Chemistry · doi:10.1021/ac60214a047 · Cited by 21,904
Soil Carbon Sequestration Impacts on Global Climate Change and Food Security
Lal, R. (2004) · Science · doi:10.1126/science.1097396 · Cited by 8,376
Cited by
Meyer, H., Reudenbach, C., Wöllauer, S., & Nauss, T. (2019) · Ecological Modelling · doi:10.1016/j.ecolmodel.2019.108815 · Cited by 509
Modelling and mapping soil organic carbon stocks in Brazil
Gomes, L. C., Faria, R. M., de Souza, E., Veloso, G. V., Schaefer, C. E. G. R., & Filho, E. I. F. (2019) · Geoderma · doi:10.1016/j.geoderma.2019.01.007 · Cited by 470
Schmid, T., Rodriguez-Rastrero, M., Escribano, P., Palacios-Orueta, A., Ben-Dor, E., Plaza, A., Milewski, R., Huesca, M., Bracken, A., Cicuendez, V., et al. (2016) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2015.2462125 · Cited by 49
Metadata
- Authors
- Stevens, A., Nocita, M., Tóth, G., Montanarella, L., & van Wesemael, B.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2013-06-19
- Volume
- 8
- Issue
- 6
- Pages
- e66409
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W1986938560
- Cited by
- 464
- References
- 3
- FWCI
- 13.08
- Type
- journal article
- Language
- en
- Open access
- gold
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- Stevens, A., Nocita, M., Tóth, G., Montanarella, L., & van Wesemael, B. (2013). Prediction of Soil Organic Carbon at the European Scale by Visible and Near InfraRed Reflectance Spectroscopy. PLoS ONE. https://doi.org/10.1371/journal.pone.0066409
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