为探讨土壤重金属含量的高光谱快速监测方法,以石家庄市水源保护区褐土为研究对象,基于土壤有机质敏感波段对应的多种光谱变换指标,采用偏最小二乘回归方法,建立了土壤重金属镉(Cd)的高光谱间接反演模型。结果表明,研究区土壤样本Cd含量平均值为0.220 mg/kg,处于严重污染水平;有机质含量与Cd含量之间显著相关,两者存在一定的吸附赋存关系;有机质原始光谱反射率对应的敏感波段为797 nm,各种光谱变换中倒数对数的一阶微分(absorbance transformation and first derivative,ATFD)与有机质含量的相关性最大,一阶微分(first derivative,FD)与有机质含量存在最大的正相关关系;基于建模和验证样本分析,多光谱变换指标偏最小二乘回归模型优于单光谱变换指标偏最小二乘模型和多光谱变换指标逐步回归模型,模型解释变量为1409 nm波段处的倒数对数的二阶微分(absorbance transformation and second derivative,ATSD)和1396 nm波段处的FD,建模和验证样本R 2分别达0.83和0.80。采用基于有机质光谱诊断特征建立多光谱变换指标集成估算模型来间接反演重金属Cd含量是可行的,所建最优模型可以为该地区重金属Cd的快速遥感监测提供参考。
Rapid determination of soil organic matter(SOM) using regression models based on soil reflectance spectral data serves an important function in precision agriculture. "Deviation of arch"(DOA)-based regression and partial least squares regression(PLSR)are two modeling approaches to predict SOM.However,few studies have explored the accuracy of the DOA-based regression and PLSR models.Therefore,the DOA-based regression and PLSR were applied to the visible near-infrared(VNIR) spectra to estimate SOM content in the case of various dataset divisions.A two-fold cross-validation scheme was adopted and repeated 10 000 times for rigorous evaluation of the DOA-based models in comparison with the widely used PLSR model.Soil samples were collected for SOM analysis in the coastal area of northern Jiangsu Province,China.The results indicated that both modelling methods provided reasonable estimation of SOM,with PLSR outperforming DOA-based regression in general.However,the performance of PLSR for the validation dataset decreased more noticeably.Among the four DOA-based regression models,a linear model provided the best estimation of SOM and a cutoff of SOM content(19.76 g kg^(-1)),and the performance for calibration and validation datasets was consistent.As the SOM content exceeded 19.76 g kg^(-1),SOM became more effective in masking the spectral features of other soil properties to a certain extent.This work confirmed that reflectance spectroscopy combined with PLSR could serve as a non-destructive and cost-efficient way for rapid determination of SOM when hyperspectral data were available.The DOA-based model,which requires only 3 bands in the visible spectra,also provided SOM estimation with acceptable accuracy.
