Prediction of soil organic carbon stock by laboratory spectral data and airborne hyperspectral images-Reference-Cited by-同舟云学术

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Prediction of soil organic carbon stock by laboratory spectral data and airborne hyperspectral images

Published:2019-03 Issue: Volume:337 Page:32-41
ISSN:0016-7061
Container-title:Geoderma
language:en
Short-container-title:Geoderma

Author:

Guo Long,Zhang Haitao,Shi Tiezhu,Chen Yiyun,Jiang Qinghu,Linderman M.

Funder

Natural Science Foundation of Hubei Province

Fundamental Research Funds for the Central Universities

Chinese Academy of Sciences

National Natural Science Foundation of China

National Undergraduate Innovation and Entrepreneurship Training Program

Publisher

Elsevier BV

Subject

Soil Science

Reference50 articles.

1. Predicting clay content on field-moist intact tropical soils using a dried, ground VisNIR library with external parameter orthogonalization;Ackerson;Geoderma,2015

2. Penetrometer-mounted VisNIR spectroscopy: application of EPO-PLS to in situ VisNIR spectra;Ackerson;Geoderma,2017

3. Predictive ability of soil properties to spectral degradation from laboratory vis-NIR spectroscopy data;Adeline;Geoderma,2017

4. Role of soil survey in obtaining a global carbon budget;Arnold,1995

5. Near-infrared (NIR) and mid-infrared (MIR) spectroscopic techniques for assessing the amount of carbon stock in soils e critical review and research perspectives;Bellonmaurel;Soil Biol. Biochem.,2011

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