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Prediction of Soil Organic Carbon Contents in Tibet Using a Visible Near-Infrared Spectral Library

  • SOIL CHEMISTRY
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Abstract

Accurate soil organic carbon (SOC) data are very important for management of agricultural production and climate change mitigation. Visible near-infrared diffuse reflectance spectroscopy is an inexpensive, non-destructive, efficient, and reliable technique for monitoring soil properties. Soil spectral libraries can contain large sets of diverse soil data for empirical calibration. In this study, we focused on improving the prediction accuracy of the SOC content at the local field scale in Tibet using field-wet, intact spectra and different spectral libraries. The direct standardization algorithm and piecewise direct standardization algorithm were used to remove the influence of environmental factors from the in situ vis-NIR spectra. These algorithms effectively removed the influence of environment factors from the field-wet, intact spectra. The ratio of performance to deviation values for prediction of the SOC content using the field and laboratory spectra with the local spectral library were 1.57 and 1.98, respectively. The local spectral library models outperformed spiked national spectral library models and had higher ratio of performance to deviation values for shrub meadows, forests, and the total dataset.

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ACKNOWLEDGMENTS

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Zhou Shi, Xiaolin Jia and Bifeng Hu. The first draft of the manuscript was written by Xiaolin Jia and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. We thank Gabrielle David, PhD, from Liwen Bianji (Edanz) (www.liwenbianji.cn/) for editing the English text of a draft of this manuscript.

Funding

This research was supported by grants from the Social Science Foundation of Jiangxi Province (Grant no. 21YJ43D), the Project of Department of Education Science and Technology of Jiangxi Province (Grant no. GJJ210541), the National Science Foundation of China (Grant nos. 42201073, 42071068), the Open Foundation of the Key Laboratory of Agricultural Remote Sensing and Information System, Zhejiang Province (Grant no. ZJRS-2022001) and the Key Laboratory of Environment Remediation and Ecological Health (Zhejiang University), Ministry of Education (Grant no. EREH202206).

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Authors and Affiliations

  1. College of Surveying and Geo-informatics, North China University of Water Resources and Electric Power, Zhengzhou, 450000, Henan, China

    Xiaolin Jia

  2. College of Tourism and Urban Management, Jiangxi University of Finance and Economics, Nanchang, 330000, Jiangxi, China

    Modian Xie, Bifeng Hu, Yin Zhou, Hongyi Li, Wanru Zhao & Wanming Deng

  3. Key Laboratory of Environment Remediation and Ecological Health (Zhejiang University), Ministry of Education, 310058, Hangzhou, China

    Bifeng Hu, Yin Zhou & Zhou Shi

  4. Institute of Land and Urban-Rural Development, Zhejiang University of Finance and Economics, 310018, Hangzhou, China

    Yin Zhou

  5. Institute of Agricultural Remote Sensing and Information Technology Application, Zhejiang University, 310058, Hangzhou, China

    Zhou Shi

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  1. Xiaolin Jia
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  2. Modian Xie
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  4. Yin Zhou
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  8. Zhou Shi
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Correspondence to Bifeng Hu.

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Jia, X., Xie, M., Hu, B. et al. Prediction of Soil Organic Carbon Contents in Tibet Using a Visible Near-Infrared Spectral Library. Eurasian Soil Sc. 56, 727–737 (2023). https://doi.org/10.1134/S1064229322601214

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  • DOI: https://doi.org/10.1134/S1064229322601214

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