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Applied and Environmental Soil Science
Volume 2012 (2012), Article ID 971252, 20 pages
doi:10.1155/2012/971252
A Comparison of Feature-Based MLR and PLS Regression Techniques for the Prediction of Three Soil Constituents in a Degraded South African Ecosystem
1Department of Land Surface, German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), Oberpfaffenhofen, 82234 Weßling, Germany
2Remote Sensing Section, Department of Geodesy and Remote Sensing, German Research Centre for Geosciences (GFZ), Telegrafenberg, 14473 Potsdam, Germany
Received 16 February 2012; Revised 20 April 2012; Accepted 21 May 2012
Academic Editor: Eyal Ben-Dor
Copyright © 2012 Anita Bayer et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
How to Cite this Article
Anita Bayer, Martin Bachmann, Andreas Müller, and Hermann Kaufmann, “A Comparison of Feature-Based MLR and PLS Regression Techniques for the Prediction of Three Soil Constituents in a Degraded South African Ecosystem,” Applied and Environmental Soil Science, vol. 2012, Article ID 971252, 20 pages, 2012. doi:10.1155/2012/971252