Monitoring soil organic carbon in alpine soils using in situ vis-NIR spectroscopy and a multilayer perceptron

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成果类型：

期刊论文

作者：

Chen, Songchao;Xu, Dongyun;Li, Shuo;Ji, Wenjun;Yang, Meihua;...

通讯作者：

Shi, Zhou

作者机构：

[Xu, Hanyi; Shi, Zhou; Chen, Songchao; Zhou, Yin; Xu, Dongyun; Yang, Meihua] Zhejiang Univ, Coll Environm & Resource Sci, Inst Appl Remote Sensing & Informat Technol, Hangzhou 310058, Peoples R China.

[Hu, Bifeng; Chen, Songchao] INRA, Unite InfoSol, Orleans, France.

[Chen, Songchao] INRA, SAS, Rennes, France.

[Li, Shuo] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat, Wuhan, Peoples R China.

[Ji, Wenjun] China Agr Univ, Coll Land Sci & Technol, Beijing, Peoples R China.

通讯机构：

[Shi, Zhou] Z

Zhejiang Univ, Coll Environm & Resource Sci, Inst Appl Remote Sensing & Informat Technol, Hangzhou 310058, Peoples R China.

语种：

英文

关键词：

deep learning;hyperparameter optimization;proximal soil sensing;Qinghai-Tibet Plateau;soil monitoring

期刊：

Land Degradation & Development

ISSN：

1085-3278

年：

2020

卷：

期：

页码：

1026-1038

DOI：

10.1002/ldr.3497

基金类别：

China Scholarship CouncilChina Scholarship Council [201606320211]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China [41571339, 41661061]

机构署名：

本校为其他机构

院系归属：

城市与环境科学学院

摘要：

Soil quality in alpine ecosystems requires regular monitoring to assess its dynamics under changes in climate and land use. Visible near‐infrared (vis‐NIR) spectroscopy could offer an option, as sampling and transporting large numbers of soil samples in the Qinghai‐Tibet Plateau is extremely difficult. However, the potential for in situ vis‐NIR spectra and the optimal algorithms need to be defined in this region. We have therefore evaluated the performance of a deep learning method, multilayer perceptron (MLP), for in situ spectral measurem...

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Monitoring soil organic carbon in alpine soils using in situ vis-NIR spectroscopy and a multilayer perceptron

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