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土壤有机质高光谱灰信息关联估测模型

车红 徐璐 曾令 李西灿

山东农业大学学报(自然科学版)2024,Vol.55Issue(5):782-788,7.
山东农业大学学报(自然科学版)2024,Vol.55Issue(5):782-788,7.DOI:10.3969/j.issn.1000-2324.2024.05.018

土壤有机质高光谱灰信息关联估测模型

Grey Information Relational Estimation Model of Soil Organic Matter Using Hyperspectral Data

车红 1徐璐 1曾令 1李西灿1

作者信息

  • 1. 山东农业大学信息科学与工程学院,山东 泰安 271018
  • 折叠

摘要

Abstract

In order to overcome the uncertainty in hyperspectral estimation,we establishes a hyperspectral grey correlated estimation model of soil organic matter content based on grey information theory.Based on 76 samples in Zhangqiu District,Jinan City,the spectral data are first transformed by mathematical methods such as logarithmic reciprocal and reciprocal logarithmic first-order differentiation,the correlation coefficient is calculated,and the estimation factors are selected by using the principle of maximum correlation.Then,according to the principle of increasing information and taking large method,the spectral estimation factors of each sample are sorted from small to large,and the grey information sequences are formed,and the grey information relational estimation model of soil organic matter content is constructed based on the information chain.Finally,the estimation results based on different information chains are fused twice,and compared with the commonly used estimation methods.The results show that the average relative error of 12 test samples is 5.576%,and the determination coefficient R2 is 0.934,and higher than that of the common methods such as the multiple linear regression,BP neural network and support vector machine and so on.The results show the grey correlated model based on grey information proposed is feasible and effective,and provides a new way for hyperspectral estimation of soil trait indicators.

关键词

土壤有机质/高光谱遥感/灰色信息关联/估测模型

Key words

Soil organic matter/Hyper-spectral remote sensing/Grey information relational/Estimation model

分类

信息技术与安全科学

引用本文复制引用

车红,徐璐,曾令,李西灿..土壤有机质高光谱灰信息关联估测模型[J].山东农业大学学报(自然科学版),2024,55(5):782-788,7.

基金项目

泰安市科技创新发展项目(2021NS090) (2021NS090)

山东省自然科学基金项目(ZR2022QG037) (ZR2022QG037)

山东农业大学学报(自然科学版)

OA北大核心CSTPCD

1000-2324

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