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成果类型:
期刊论文
作者:
Hong, Yongsheng;Sanderman, Jonathan;Hengl, Tomislav;Chen, Songchao;Wang, Nan;...
通讯作者:
Shi, Z
作者机构:
[Hong, Yongsheng] Chinese Acad Sci, Inst Soil Sci, State Key Lab Soil & Sustainable Agr, Nanjing 210008, Peoples R China.
[Hong, Yongsheng] Univ Chinese Acad Sci, Beijing 100049, Peoples R China.
[Sanderman, Jonathan] Woodwell Climate Res Ctr, Falmouth, MA 02540 USA.
[Hengl, Tomislav] OpenGeoHub Fdn, Agro Business Pk 10, NL-6708 PW Wageningen, Netherlands.
[Chen, Songchao] ZJU Hangzhou Global Sci & Technol Innovat Ctr, Hangzhou 311200, Peoples R China.
通讯机构:
[Shi, Z ] Z
Zhejiang Univ, Inst Agr Remote Sensing & Informat Technol Applica, Coll Environm & Resource Sci, Hangzhou 310058, Peoples R China.
语种:
英文
关键词:
Soil monitoring;Mid-infrared spectroscopy;Soil spectral library;Fractional-order derivative;Deep learning
期刊:
CATENA
ISSN:
0341-8162
年:
2024
卷:
235
页码:
107628
基金类别:
National Natural Science Foundation of China [42201058]; National Key Research and Development Program of China [2022YFB3903503]; Research Foundation-Flanders [G0F9216N]; China Postdoctoral Science Foundation [2021M702840]; Food and Agriculture Cyber-informatics Tools Coordinated Innovation Network NIFA - USDA National Institute of Food and Agriculture; [2020-67021-32467]
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:
Accurate monitoring of soil organic carbon (SOC) is critical for sustainable management of soil for improving its quality, function, and carbon sequestration. As a nondestructive, efficient, and low-cost technique, mid-infrared (MIR) spectroscopy has shown a great potential in rapid estimation of SOC, despite limited studies of the global scale. The objective of this work was to use a globally distributed topsoil MIR spectral library with 33,039 samples to predict SOC using different modeling methods. Effects of nine fractional-order derivatives (FODs) on the predicted accuracy of SOC were eva...

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