Prediction Accuracy of Soil Organic Carbon from Ground Based Visible Near-Infrared Reflectance Spectroscopy
Author:
Publisher
Springer Science and Business Media LLC
Subject
Earth and Planetary Sciences (miscellaneous),Geography, Planning and Development
Link
http://link.springer.com/article/10.1007/s12524-017-0744-0/fulltext.html
Reference31 articles.
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2. Bellon-Maurel, V., Fernandez-Ahumada, E., Palagos, P., Roger, J. M., & McBratney, A. B. (2010). Critical review of chemometric indicators commonly used for assessing the quality of the prediction of soil attributes by NIR spectroscopy. Trends in Analytical Chemistry, 29, 1073–1108. https://doi.org/10.1016/j.soilbio.2011.02.019.
3. Buddenbaum, H., & Steffens, M. (2012). The effects of spectral pretreatments on chemometric analyses of soil profiles using laboratory imaging spectroscopy. Applied and Environmental Soil Science, 274903, 12. https://doi.org/10.1155/2012/274903.
4. Chang, C. W., Laird, D. A., Mausbach, M. J., & Hurburgh, C. R. (2001). Near-infrared reflectance spectroscopy—principal components regression analyses of soil properties. Soil Science Society of America Journal, 65, 480–490.
5. Chiang, Y. M., Chang, L. C., & Chang, F. J. (2004). Comparison of static feedforward and dynamic-feedback neural networks for rainfall runoff modeling. Journal of Hydrology, 290, 297–311. https://doi.org/10.1016/j.jhydrol.2003.12.033.
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