摘要
以实验室内测取的土壤反射光谱为研究对象,利用PLSR方法建立反射光谱与土壤As含量之间的模型,通过交叉验证、估算检验建模精度,探讨利用反射光谱估算土壤As含量的可行性。通过比较不同光谱预处理方法、不同光谱分辨率和不同OM含量条件下建模、验证和估算结果。表明,MSC方法可以有效去除散射的影响而取得较好的结果(估算R2=0.711,RPD=1.827,RMSEP=1.613),不同光谱分辨率结果均较优(估算0.678<R2<0.711,1.750<RPD<1.827,1.613<RMSEP<1.685),低OM含量样本结果(估算R2=0.694,RPD=1.697,RMSEP=1.644)好于高OM含量样本。研究结果表明可以利用反射光谱估算土壤中As含量,通过各种光谱预处理方法提高估算精度,为进行土壤污染监测提供新的技术方法。
In the present study,visible-near infrared reflectance spectroscopy（VNIR） measured in laboratory was evaluated for prediction of the content of As in soils.Calibrations between As and reflectance were developed using cross-validation under partial least squares regression（PLSR）.Prediction accuracy was tested via separate validation samples.The reflectance was pre-processed by several techniques like smoothing,multiplicative scatter correction（MSC）,Log（1/R）,first/second derivative（F/SD） and continuum removal（CR）.The accuracy of prediction was evaluated with three statistics：coefficients of determination（R2）,ratio of performance to deviation（RPD）,and root mean square error of prediction（RMSEP）.The results of calibration,cross-validation and prediction of different pre-processing techniques,spectral resolution and OM content were compared.MSC provided better prediction（Prediction R2=0.711,RPD=1.827,RMSEP=1.613） than other methods because it removed the effects of light scattering and sample thickness.All the results of different resolution are acceptable（Prediction 0.678R20.711,1.750RPD1.827,1.613RMSEP1.685）.The prediction accuracy of subsets with lower OM content（Prediction R2=0.694,RPD=1.697,RMSEP=1.644） was better than that with higher content.The study indicates that it is feasible to predict As element in soils using reflectance spectroscopy and the prediction accuracy can be improved by pre-processing.Thus this new rapid and cost-effective technique can be used in the monitoring of soil contamination.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2011年第1期173-176,共4页
Spectroscopy and Spectral Analysis
基金
国家重点基础研究发展规划(973)项目(2002CB410810)
江苏农用地质量动态监测研究项目(2004LY001)资助
关键词
反射光谱
砷
土壤污染
PLSR
Reflectance spectroscopy
As
Soil contamination
PLSR
