Spectral testing and quantitative inversion for dust of iron tailings on leaf
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摘要: 目前我国累计堆存的铁尾矿量高达约50亿t,所产生的尾矿粉尘污染极其严重.为此,使用辽宁鞍山矿区铁尾矿粉尘进行实景观测实验,采用人工模拟降尘与光谱测量手段,研究了降尘量对植物叶片光谱的影响规律;并利用降尘量与植物叶片光谱相关性最好的优势波段与铁元素的光谱吸收特征,分别建立了叶面降尘量的基于植物叶片的优势波段反射率和基于铁元素的独特光谱吸收指数的2种定量反演模型.研究表明:随着铁尾矿粉尘降尘量逐渐增大,植物叶片反射光谱曲线与粉尘的光谱曲线差异逐渐减小;2种反演方式中降尘量与植物叶片光谱变量均呈极显著相关,但基于铁元素光谱吸收特征的定量反演模型精度更高.研究结果可为高光谱遥感应用于矿区降尘量定量监测提供基础模型与技术依据.Abstract: In China,iron tailings dumps have been accumulated up to about 5 billion tons.The tailings have led to extremely serious dust pollution.Therefore,dust effects on leaf spectra were studied on the basis of the observation of real experiments with Anshan mine tailings dust and by means of artificial simulated dust and spectral measurements.The dust samples of iron tailings were taken from the Anshan mining area.The quantitative inversion of foliar dustfall was realized by using the band of the best correlation between the dustfall and the vegetation leaf spectrum and the characteristics of absorption spectra of iron respectively.The results show that,when the dustfall of iron tailings on leaf increased,the differences of spectral curve between leaf and dust decreased.In the two inversion methods,dustfall and vegetation leaf spectral variables were significantly related to each other.Furthermore,the precision of the inversion modeling according to spectral characteristics of iron is higher than that of the one according to best correlation band.The results could provide basic model and technical basis for quantifying the amount of mining dust monitoring with hyperspectral remote sensing.
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Key words:
- foliar dustfall /
- iron tailings /
- hyperspectral inversion /
- spectral absorption index
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