矿区农田土壤砷污染的可见-近红外反射光谱分析研究

利用在实验室获取的矿区农田土壤可见-近红外反射光谱与土壤As污染浓度、Fe和有机质含量数据构建了As和Fe浓度及有机质含量的PCR与PLSR预测模型;为提高模型的稳定性和预测能力，对原始光谱数据进行了预处理即，一和二阶微分(F/SD)、基线校正(B)、变量标准规一化(SNV)、多次散射校正(MSC)和连续统去除(CR)。研究表明：变量标准规一化(SNV)、多次散射校正(MSC)和连续统去除(CR)分别对As, Fe和OM的PCR模型的预测能力有明显的改善(各PCR模型的因子数、相对RMSEP和R2分别5，0.304 0，0.368 5;3，0.144 3，0.476 2和3，0.171 2，0.408 4)。预测As和Fe浓度及有机质含量的最优PCR模型使用了一些共同的波段：450, 1 000, 1 400, 1 900, 2 050, 2 200, 2 250, 2 400和2 470 nm。因此，可以通过遥感技术来检测土壤污染物浓度及其他物质含量，从而为土壤环境质量的遥感监测提供参考。

Analysis of Visible and Near-Infrared Spectra of As-Contaminated Soil in Croplands Beside Mines

Soil samples in the depth from 0 to 20 cm were scooped from agricultural region beside mines and prepared for determination of As concentration,Fe concentrations and organic matter content.At the same time they were scanned by mobile hyperspectral radiometer for visible and near-infrared spectra.Savitzky-Golay filter was used to smooth noises in spectrum curve because of some low signal-to-noise ratios in some regions of visible and near-infrared light,and all the spectra were resampled with the spectral in...