Rapid identification of soil organic matter level via visible and near-infrared spectroscopy: Effects of two-dimensional correlation coefficient and extreme learning machine

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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：

Hong, Yongsheng;Chen, Songchao;Zhang, Yong;Chen, Yiyun*;Yu, Lei;...

通讯作者：

Chen, Yiyun;Liu, Yanfang

作者机构：

[Hong, Yongsheng; Chen, Yiyun; Liu, Yanfang; Cheng, Hang; Liu, Yaolin; Liu, Yi] Wuhan Univ, Sch Resource & Environm Scrences, Wuhan 430079, Hubei, Peoples R China.

[Hong, Yongsheng; Cheng, Hang; Chen, Yiyun; Liu, Yi] Chinese Acad Sci, State Key Lab Soil & Sustainable Agr, Nanjing 210008, Jiangsu, Peoples R China.

[Chen, Songchao] INRA, Unite InfoSol, F-45075 Orleans, France.

[Chen, Songchao] INRA, UMR SAS, Agrocampus Ouest, F-35042 Rennes, France.

[Zhang, Yong] Anhui Univ Finance & Econ, Sch Publ Finance & Adm, Bengbu 233030, Peoples R China.

通讯机构：

[Chen, YY; Liu, YF] W

Wuhan Univ, Sch Resource & Environm Scrences, Wuhan 430079, Hubei, Peoples R China.

语种：

英文

关键词：

Correlation coefficient;Machine learning model;Remote sensing;Soil organic matter fertility level

期刊：

Science of The Total Environment

ISSN：

0048-9697

年：

2018

卷：

644

页码：

1232-1243

DOI：

10.1016/j.scitotenv.2018.06.319

基金类别：

National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [41771440, 41501444]

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 estimation of soil organic matter (SOM) is essential in understanding the spatial distribution of SOM to identify areas that need fertilization and the required grade of those fertilizers. Visible and near-infrared spectroscopy is a promising alternative to time consuming and costly conventional soil assessment methods. However, this approach is highly dependent on selecting suitable preprocessing strategies and data mining techniques for regression analysis. In this study, 2D correlation coefficients, including ratio, difference, and normalized difference indices, were introduced to ...

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Rapid identification of soil organic matter level via visible and near-infrared spectroscopy: Effects of two-dimensional correlation coefficient and extreme learning machine

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