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In-situ prediction of soil organic carbon by vis–NIR spectroscopy : an efficient use of limited field data

Title data

Kühnel, Anna ; Bogner, Christina:
In-situ prediction of soil organic carbon by vis–NIR spectroscopy : an efficient use of limited field data.
In: European Journal of Soil Science. Vol. 68 (2017) Issue 5 . - pp. 689-702.
ISSN 1351-0754
DOI: https://doi.org/10.1111/ejss.12448

Abstract in another language

Visible–near-infrared diffuse reflectance spectroscopy (vis–NIR DRS) has been widely used to predict soil organic carbon (SOC) in the laboratory. Predictions made directly from soil spectra measured in situ under field conditions, however, remain challenging. This study addresses the issue of incorporating in-situ reflectance spectra efficiently into calibration data when a few field measurements only are available. We applied the synthetic minority oversampling technique (SMOTE) to generate new data with in-situ reflectance spectra from soil profiles. Subsequently, we combined existing spectral libraries with these new synthetic data to predict SOC by partial least squares regression (PLSR). We found that models with added synthetic spectra always outperformed models based on the spectral libraries alone and in most cases also those with added in-situ spectra only. We used the models to predict the distribution of SOC in soil profiles under five different land uses at Mount Kilimanjaro (Tanzania). Based on our results, we propose a framework for predicting SOC with a limited number of in-situ soil spectra. This framework could effectively reduce the costs of developing in-situ models for SOC at the local scale.

Further data

Item Type: Article in a journal
Refereed: Yes
Additional notes: BAYCEER140840
Institutions of the University: Research Institutions
Research Institutions > Research Centres
Research Institutions > Research Centres > Bayreuth Center of Ecology and Environmental Research- BayCEER
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences > Chair Ecological Modelling
Faculties
Faculties > Faculty of Biology, Chemistry and Earth Sciences
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences
Result of work at the UBT: Yes
DDC Subjects: 500 Science
Date Deposited: 09 Jan 2018 08:28
Last Modified: 09 Jan 2018 08:28
URI: https://eref.uni-bayreuth.de/id/eprint/41214