重金属含量的高光谱建模反演:考古土壤中的应用

摘要

This paper, based on the rapid and nondestructive testing of hyperspectral reflectance compared with conventional methods, constructed hyperspectral models for retrieving soil heavy metal content in different historical period by correlation analysis and multivariable statistical method. The result shows that the correlation between content of Cd, Cr, Cu, Ni,Pb and hyperspectral reflectance of 400 ～ 550nm and 1000 ～ 2500nm is more distinguished than other bands, and that the correlation enhanced remarkably after the original spectra derivate transformed. The first derivate stepwise linear regression model is optimal for retrieving soil heavy metal content in different period, with a minimum determination coefficient of 0.92and maximum RMSE of 1.83. The relationship of As with reflectance spectra was affected by ferriferous oxides, organic matter and carbonate mineral; of Cd, Cu and Ni, by ferriferous oxides, clay mineral and organic matter, respectively; of Cr, by many factors; and of Pb, by both ferriferous oxides and clay mineral.%基于反射高光谱快速、无损的检测优势,以不同历史时期考古土壤作为光谱信息来源,应用相关分析和多元变量统计方法,构建了历史时期土壤重金属含量的高光谱反演模型.结果表明,Cd、Cr、Cu、Ni和Pb含量与原始光谱在400～550nm和1000～2500nm存在显著相关,微分转换有助于提取土壤中重金属元素信息.一阶微分光谱的多元线性逐步回归模型为反演历史时期土壤重金属含量的最佳模型,其判定系数最小为0.92,均方根误差最大为1.83.As与反射光谱相关性受到铁的氧化物、有机质及碳酸盐类矿物的影响;Cd、Cu和Ni主要受到铁的氧化物、粘土矿物和有机质的影响;Cr则受多种因素综合作用,情况较复杂;Pb主要受到铁的氧化物和粘土矿物的影响.