含水率对土壤有机质含量高光谱估算的影响

土壤含水率对有机质（soil organic matter，SOM）含量高光谱估算精度有很大的影响。为了探讨SOM高光谱估算中土壤含水率的影响，该文对烘干土、风干土和质量含水率为5%～40%（按5%递增）的土壤样本进行了室内高光谱测量，对光谱数据进行了反射率、反射率一阶导数和反射率倒数对数3种光谱数据变换，运用偏最小二乘回归法（partial least squares regression，PLSR）建立了相应的SOM估算模型。结果表明，风干土的SOM高光谱估算精度较好；当含水率水平小于25%时，SOM估算模型精度受含水率的影响较大，光谱数据进行反射率倒数对数变换后的模型精度最高；当含水率水...

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Bibliographic Details
Published in农业工程学报 Vol. 31; no. 9; pp. 114 - 120
Main Author 司海青 姚艳敏 王德营 刘影
Format Journal Article
LanguageChinese
Published 中国农业科学院农业资源与农业区划研究所，北京 100081 2015
农业部农业信息技术重点实验室，北京 100081
Subjects
偏最小二乘
回归
土壤
土壤含水率
有机质
高光谱
soil moisture
regression analysis
hyperspectral
有机质
organic matter
土壤含水率
soils
partial least squares
偏最小二乘
回归
土壤
高光谱
Online AccessGet full text
ISSN1002-6819
DOI10.11975/j.issn.1002-6819.2015.09.018

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Summary:土壤含水率对有机质（soil organic matter，SOM）含量高光谱估算精度有很大的影响。为了探讨SOM高光谱估算中土壤含水率的影响，该文对烘干土、风干土和质量含水率为5%～40%（按5%递增）的土壤样本进行了室内高光谱测量，对光谱数据进行了反射率、反射率一阶导数和反射率倒数对数3种光谱数据变换，运用偏最小二乘回归法（partial least squares regression，PLSR）建立了相应的SOM估算模型。结果表明，风干土的SOM高光谱估算精度较好；当含水率水平小于25%时，SOM估算模型精度受含水率的影响较大，光谱数据进行反射率倒数对数变换后的模型精度最高；当含水率水平大于等于25%时，水分对土壤光谱反射率的影响要大于SOM，不适宜利用土壤光谱数据进行SOM含量高光谱估算。该研究可为大田环境不同含水率情况下光谱估算SOM提供参考。
Bibliography:11-2047/S
Soil moisture content has great influence on the prediction accuracy of soil organic matter （SOM） content using hyperspectral data. The purpose of this study was to find the threshold of soil moisture content suitable for using hyperspectral data to predict SOM content. A total of 63 soil samples including black soil, chernozem and meadow soil were collected from crop fields in Lishu and Gongzhuling county, Jilin province and in Binxin county, Heilongjiang province. The soil samples were air-dried and sieved through a 2-mm sieve. SOM contents were measured in the laboratory. The soil samples were divided into two groups including 42 samples for calibration and 21 for validation. Reflectance of soil samples with over-dried, air-dried and 5% to 40% soil moisture contents （the interval of 5%） were measured using ASD Fieldspec Pro High Spectrometer in a dark room. Soil spectral reflectance （R） was mathematically transformed into first derivatives of reflectance （R’） and the logarithm of the inverse of th
ISSN:1002-6819
DOI:10.11975/j.issn.1002-6819.2015.09.018