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Mogens Humlekrog Greve

Soil profile organic carbon prediction with Visible Near Infrared Reflec-tance spectroscopy based on a national database

Publikation: KonferencebidragPaperForskning

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Soil profile organic carbon prediction with Visible Near Infrared Reflec-tance spectroscopy based on a national database. / Deng, Fan; Knadel, Maria; Peng, Yi; Heckrath, Goswin Johann; Minasny, B. ; Greve, Mogens Humlekrog.

2012. Paper præsenteret ved 5'th global workshop on Digital Soil Mapping 2012, Sydney, Australien.

Publikation: KonferencebidragPaperForskning

Harvard

APA

Deng, F., Knadel, M., Peng, Y., Heckrath, G. J., Minasny, B., & Greve, M. H. (2012). Soil profile organic carbon prediction with Visible Near Infrared Reflec-tance spectroscopy based on a national database. Paper præsenteret ved 5'th global workshop on Digital Soil Mapping 2012, Sydney, Australien.

CBE

Deng F, Knadel M, Peng Y, Heckrath GJ, Minasny B, Greve MH. 2012. Soil profile organic carbon prediction with Visible Near Infrared Reflec-tance spectroscopy based on a national database. Paper præsenteret ved 5'th global workshop on Digital Soil Mapping 2012, Sydney, Australien.

MLA

Vancouver

Deng F, Knadel M, Peng Y, Heckrath GJ, Minasny B, Greve MH. Soil profile organic carbon prediction with Visible Near Infrared Reflec-tance spectroscopy based on a national database. 2012. Paper præsenteret ved 5'th global workshop on Digital Soil Mapping 2012, Sydney, Australien.

Author

Bibtex

@conference{a8e16dec840b4581b19a3ae25044281d,
title = "Soil profile organic carbon prediction with Visible Near Infrared Reflec-tance spectroscopy based on a national database",
abstract = "This study focuses on the application of the Danish national soil Visible Near Infrared Re-flectance spectroscopy (NIRs) database for predicting SOC in a field. The Conditioned Latin hypercube sam-pling (cLHS) method was used for the selection of 120 soil profiles based on DualEM21s and DEM data (ele-vation, slope, profile curvature). All the soil profile cores were taken by a 1 m long hydraulic auger with plastic liners inside. A Labspec 5100 equipped with a contact probe was used to acquire spectra at (350-2500 nm) in each 5 cm depth interval. The results show that after the removal of moisture effect using an external parameter orthogonalisation algorithm, most of the spectra collected at field moisture content can be projected in the National spectra library. Moreover, the prediction of SOC improved compared to the model based on absorbance spectra.",
author = "Fan Deng and Maria Knadel and Yi Peng and Heckrath, {Goswin Johann} and B. Minasny and Greve, {Mogens Humlekrog}",
year = "2012",
language = "English",
note = "5'th global workshop on Digital Soil Mapping 2012 ; Conference date: 10-04-2012 Through 13-04-2012",

}

RIS

TY - CONF

T1 - Soil profile organic carbon prediction with Visible Near Infrared Reflec-tance spectroscopy based on a national database

AU - Deng, Fan

AU - Knadel, Maria

AU - Peng, Yi

AU - Heckrath, Goswin Johann

AU - Minasny, B.

AU - Greve, Mogens Humlekrog

PY - 2012

Y1 - 2012

N2 - This study focuses on the application of the Danish national soil Visible Near Infrared Re-flectance spectroscopy (NIRs) database for predicting SOC in a field. The Conditioned Latin hypercube sam-pling (cLHS) method was used for the selection of 120 soil profiles based on DualEM21s and DEM data (ele-vation, slope, profile curvature). All the soil profile cores were taken by a 1 m long hydraulic auger with plastic liners inside. A Labspec 5100 equipped with a contact probe was used to acquire spectra at (350-2500 nm) in each 5 cm depth interval. The results show that after the removal of moisture effect using an external parameter orthogonalisation algorithm, most of the spectra collected at field moisture content can be projected in the National spectra library. Moreover, the prediction of SOC improved compared to the model based on absorbance spectra.

AB - This study focuses on the application of the Danish national soil Visible Near Infrared Re-flectance spectroscopy (NIRs) database for predicting SOC in a field. The Conditioned Latin hypercube sam-pling (cLHS) method was used for the selection of 120 soil profiles based on DualEM21s and DEM data (ele-vation, slope, profile curvature). All the soil profile cores were taken by a 1 m long hydraulic auger with plastic liners inside. A Labspec 5100 equipped with a contact probe was used to acquire spectra at (350-2500 nm) in each 5 cm depth interval. The results show that after the removal of moisture effect using an external parameter orthogonalisation algorithm, most of the spectra collected at field moisture content can be projected in the National spectra library. Moreover, the prediction of SOC improved compared to the model based on absorbance spectra.

M3 - Paper

ER -