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《Journal of Henan Agricultural Sciences》 2018-07
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Monitoring of Heavy Metals in Soils Based on Statistical Characteristics and Hyperspectra——A Case Study of Cu

XU Xibo;ZHANG Senlin;BU Fansheng;LIU Yuhong;College of Geography and Environment,Shandong Normal University;Jiaozhou No.2 Middle School of Shandong Province;Wulian County Land Resources Bureau of Shandong Province;  
In order to accurately and efficiently monitor the heavy metal content in soil and solve the problems of high cost and low efficiency of traditional soil geochemical tests,the copper elements in the plain soil of northern Weifang were taken as an example. The first derivative conversions and actual measurements of the hyperspectral data of 52 soil samples were performed,and correlation analysis of them was done,obtaining characteristic bands sensitive to copper in soil,and using them as independent variables,measured copper content as dependent variable,establishing multivariate stepwise regression( MLR) and partial least squares( PLS) estimate model. The results showed that based on the statistical description of the heavy metal content in the soil,it was found that there was a slight copper accumulation in the area with a large range and wide coverage. The main cause was human disturbance; 12 features were extracted according to the order of Pearson's correlation coefficient. In the band,the center wavelengths were at385,667,729,731,791,802,822,834,840,841,870,873 nm,respectively; the R2 of the MLR model andthe PLS model established using the first-order derivative spectral transformation information were 0. 538 and 0. 858,the relative analysis error RPD was respectively 0. 4 and 1. 6. In comparison,the PLS model had the highest prediction accuracy,which could better monitor the content of copper in the soil,and also provided the spectral monitoring of other heavy metal elements.
【Fund】: 国家自然科学基金项目(41371395);; 河口海岸学国家重点实验室开放基金项目(SKLEC-KF201710);; 山东师范大学大学生创新创业训练计划项目(201610445013)
【CateGory Index】: X833
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