Assessment and Analysis of Migrations of Heavy Metal Lead and Zinc in Soil with Hyperspectral Inversion Model
TAO Chao1*, WANG Ya-jin1, ZOU Bin1, 2, TU Yu-long1, JIANG Xiao-lu1
1. The Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Center South University), Ministry of Education, School of Geoscience and Info-physics, Changsha 410083, China
2. Chinese National Engineering Research Center for Control & Treatment of Heavy Metal Pollution, Changsha 410083, China
Abstract：The existing model of soil heavy metal content reversal model by hyperspectral remote sensing technology is mostly based on the limited sample points of the same study area. However, considering the practical application requirements, whether the model has a good migrate ability is an urgent question. If it is not feasible, is there any other feasible means for soil heavy metal pollution assessment? In order to answer the above-mentioned questions, this paper selects two lead-zinc mines in Chenzhou City and Hengyang City as research areas. The quantitative inversion and qualitative classification of heavy metals Pb and Zn were carried out using the sampling sites in Chenzhou area to compare the two models in Hengyang City of the migrate ability. Experiments show that: (1) Quantitative inversion model based on Partial least squares regression (PLSR) has poor migration ability. The regression model was established by four spectral preprocessing methods. It was found that the prediction accuracy of the model was very low, and it was difficult to correctly invert the contents of Pb and Zn in Hengyang research area. (2) Support vector machine (SVM) classification of qualitative inversion model has a certain ability to migrate. Based on Chenzhou area sampling data, training SVM classification model can effectively predict the Hengyang research area Pb and Zn pollution situation, the prediction accuracies are 84.78% and 86.96%, respectively. The results show that qualitative classification is a more practical way to detect soil heavy metal pollution rapidly.
Key words：Heavy metal pollution; Hyperspectral; Migration analysis; SVM classification; Partial least squares regression
陶 超，王亚晋，邹 滨，涂宇龙，姜晓璐. 土壤重金属铅、锌高光谱反演模型可迁移能力分析研究[J]. 光谱学与光谱分析, 2018, 38(06): 1850-1855.
TAO Chao, WANG Ya-jin, ZOU Bin, TU Yu-long, JIANG Xiao-lu. Assessment and Analysis of Migrations of Heavy Metal Lead and Zinc in Soil with Hyperspectral Inversion Model. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1850-1855.
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