期刊论文

Li, S

中文

红外与毫米波学报

1001-9014

2023

42

6

816-824

10.11972/j.issn.1001-9014.2023.06.015

Young Scientists Fund of the National Natural Science Foundation of China [41601370]; Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture and Rural Affairs, P. R. China [2022ZJUGP003]; Fundamental Research Funds for the Central Universities [CCNU22JC022]

本校为第一且通讯机构

土壤中红外（MIR）光谱能快速、无污染、低成本地估算土壤有机碳等理化属性。随着各种尺度土壤光谱库的建立，使用其进行快速土壤分析引起广泛关注，但光谱库的通用模型在局部尺度上的预测效果不理想。开发“局部化”光谱建模方法是提高土壤光谱库性能的有效途径。本文提出了一种新的方法，通过光谱相似度计算和建模子集构建，旨在从库中快速建立最优局部建模集以提高预测精度。比较了欧氏、马氏、余弦三种距离算法衡量待测样本与库样本之间的相似度并生成距离矩阵；使用连续统去除法从距离矩阵中提取库容曲线中的特征点。利用偏最小二乘回归建立土壤MIR光谱与有机碳含量间的定量关系。结果表明...

Soil mid-infrared(MIR)can provide a rapid,non-polluting,and cost-efficient method for estimating soil properties,such as soil organic carbon(SOC).Although there is a wide interest in using the soil spectral library(SSL)for soil analysis at various scales,the SSL with a ...MORE Soil mid-infrared(MIR)can provide a rapid,non-polluting,and cost-efficient method for estimating soil properties,such as soil organic carbon(SOC).Although there is a wide interest in using the soil spectral library(SSL)for soil analysis at various scales,the SSL with a ge...