Strategies for predicting soil organic matter in the field using the Chinese Vis-NIR soil spectral library

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作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Yang, Meihua;Chen, Songchao;Xu, Dongyun;Hong, Yongsheng;Li, Shuo;...

通讯作者：

Chen, Songchao(chensongchao@zju.edu.cn)

作者机构：

[Yang, Meihua] Yuzhang Normal Univ, Dept Environm Engn, Nanchang 330103, Peoples R China.

[Chen, Songchao] Zhejiang Univ, ZJU Hangzhou Global Sci & Technol Innovat Ctr, Hangzhou 311215, Peoples R China.

[Hong, Yongsheng; Shi, Zhou; Chen, Songchao] Zhejiang Univ, Inst Appl Remote Sensing & Informat Technol, Coll Environm & Resource Sci, Hangzhou 310058, Peoples R China.

[Xu, Dongyun] Shandong Agr Univ, Coll Resources & Environm, Tai An 271000, Peoples R China.

[Li, Shuo] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Peoples R China.

通讯机构：

[Songchao Chen] Z

ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou 311215, China<&wdkj&>Institute of Applied Remote Sensing and Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China

语种：

英文

关键词：

Vis-NIR spectroscopy library;Soil organic matter;In situ spectra;Memory-based learning;Squared Euclidean distance

期刊：

Geoderma

ISSN：

0016-7061

年：

2023

卷：

433

页码：

116461

DOI：

10.1016/j.geoderma.2023.116461

基金类别：

This research was supported by the National Natural Science Foundation of China (No. 42201054), the Natural Science Foundation of Jiangxi Province (No. 20212BAB205022), and the Science and Technology Research Project of Jiangxi Provincial Department of Education (No. GJJ181150).

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：

The large-scale soil spectral library (SSL) can provide abundant information for predicting soil properties at a local scale, especially in places lacking data. However, since all the existing large-scale SSLs only contain dry spectra recorded under laboratory conditions, the challenge remains in using SSL for predicting soil information using in situ soil spectra. Previous studies have focused on the methods of transforming in situ spectra to dry spectra when using SSLs, while few studies have compared which strategies are optimal in predictin...

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Strategies for predicting soil organic matter in the field using the Chinese Vis-NIR soil spectral library

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