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Proceedings Paper

Use of imaging spectroscopy to assess different organic carbon fractions of agricultural soils
Author(s): Michael Vohland; Monika Harbich; Oliver Schmidt; Thomas Jarmer; Christoph Emmerling; Sören Thiele-Bruhn
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Paper Abstract

The site for this study - located in Rhineland-Palatinate, Germany ("Bitburger Gutland") - covered different geological substrates and agro-pedological zones. In total, 42 plots were sampled in the field; soil samples from the top horizon were analysed in the laboratory for total organic carbon (OC), hot water-extractable C (HWE-C) and microbial C (Cmic). In parallel to the ground campaign, a data set of the HyMapTM airborne imaging sensor was acquired on 27th of August 2009. After pre-processing, HyMap spectra were used to assess the contents of OC, HWE-C and Cmic. As calibration method we used partial least squares regression (PLSR), as it allows a handling of large input spaces and noisy patterns. Since calibration quality was poor for HWE-C and Cmic (cross-validated r2 values were less than 0.5), we additionally combined PLSR with a genetic algorithm (GA) to preselect an optimum set of spectral features instead of using the full spectrum. With this GA-PLSR approach, results improved considerably for all constituents in the crossvalidation (r2 ≥ 0.72). Very similar GA selection patterns for all carbon fractions suggest that spurious (indirect) correlations may be relevant for assessing HWE-C and Cmic. For the GA approach, some overfitting due to a selection based on chance correlations between C fractions and spectral variables cannot be excluded.

Paper Details

Date Published: 7 October 2011
PDF: 7 pages
Proc. SPIE 8174, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII, 81741E (7 October 2011); doi: 10.1117/12.898489
Show Author Affiliations
Michael Vohland, Univ. Trier (Germany)
Monika Harbich, Univ. Trier (Germany)
Oliver Schmidt, Univ. Trier (Germany)
Thomas Jarmer, Univ. Osnabrueck (Germany)
Christoph Emmerling, Univ. Trier (Germany)
Sören Thiele-Bruhn, Univ. Trier (Germany)


Published in SPIE Proceedings Vol. 8174:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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