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矿区土壤环境问题日益突出,以山东省烟台市焦家式金矿区为典型区,系统采集了85个表层土壤样品进行野外光谱实测,其中35份用于重金属铬含量测定。利用光谱变换技术对原始光谱提取了一阶微分、二阶微分和去包络线三种光谱指标,采用偏最小二乘回归法建立光谱数据与铬含量间的定量关系,将最优预测模型应用于其余50个样本点铬浓度值的获取,最终通过克里金插值实现了对研究区土壤重金属铬的快速监测。结果表明,基于一阶微分数据模型预测精度最高,其次为二阶微分,原始光谱和去包络线数据。研究区铬的含量与金矿的分布情况密切相关,即金矿密集区域铬含量更高,这表明金矿开采对土壤中铬的含量与分布存在一定影响。
The soil environmental problems in the mining area have become increasingly prominent. Taking the Jiaojia gold mine in Yantai City, Shandong Province as a typical area, 85 surface soil samples were collected for field measurement. 35 of them were used for the determination of chromium in heavy metals. The first-order differential, second-order differential and de-envelope spectral indices were extracted from the original spectra by using the spectral transformation technique. Partial least squares regression was used to establish the quantitative relationship between spectral data and chromium content. The optimal prediction model was applied Chromium concentration was obtained from the remaining 50 samples. Finally, Kriging interpolation was used to achieve rapid monitoring of heavy metal chromium in the study area. The results show that the prediction accuracy based on first-order differential data model is the highest, followed by the second-order differential, original spectra and de-envelope data. The chromium content in the study area is closely related to the distribution of gold ore, ie, the chromium content in the gold-rich area is higher, indicating that the gold mining affects the chromium content and distribution in the soil.