基于高光谱技术的黑土地微量金属元素探测方法及地学意义

在土壤中重金属含量较低的情况下,重金属的高光谱特征响应非常微弱,不易构建精确的高光谱直接反演模型.为了解决上述问题,依据土壤化学变量间的理化性质,将重金属富集特征转移到与之相关的化学主量元素上,使重金属微弱的信息得以间接定量反演.文中以海伦市黑土土壤为研究对象,通过主成分分析、 聚类分析确定了主量元素氧化铁(Fe2O3...

A detection method of trace metal elements in black soil based on hyperspectral technology: Geological implications

In the case of low content of heavy metals in soil, the hyperspectral characteristic response of heavy metals is very weak, so it is difficult to construct an accurate direct hyperspectral inversion model. In order to solve the above problems, according to the physical and chemical properties of soil chemical variables, the enrichment characteristics of heavy metals are transferred to the related major chemical elements, so that the weak information of heavy metals can be indirectly quantitatively inverted. In this paper, the black soil in Hailun was taken as the research object. Through principal component analysis and cluster analysis, it was confirmed that there was an obvious adsorption occurrence relationship between the major element iron oxide (Fe₂O₃) and trace heavy metals As, Zn, Cd. The best inversion model of iron oxide content in the study area was established by partial least square method (the determination coefficient is 0.704, the root mean square difference is 0.148, and the F-test is 12.732). Based on the occurrence relationship between iron oxide and As, Zn, CD, a nonlinear fitting model between the predicted value of iron oxide and the real value of heavy metals was constructed by neural network. The fitting results show that the fitting degree of As, Zn and Cd is As>Zn>Cd. The overall correlations are 0.796, 0.732, 0.530 respectively. The study results show that the indirect prediction model based on iron oxide content can better quantitatively predict As, Zn and Cd, which provides a new method for the quantitative analysis of trace heavy metal content. This model provides a basis for hyperspectral remote sensing technology to predict soil heavy metal content, enhances the feasibility of soil trace heavy metal inversion, and is helpful to refine the quality monitoring of natural resource. It is of great significance to deepen the comprehensive analysis and evaluation of geoscience system.