植物叶面铁尾矿粉尘光谱测试与定量反演实验

发布时间：2019-05-09 13:06

【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]:At present, the accumulative amount of iron tailings accumulated in our country is about 5 billion t, and the dust pollution from tailings is very serious. For this reason, the real observation experiment of iron tailings dust in Anshan mining area of Liaoning Province was carried out, and the influence of dust reduction on the spectrum of plant leaves was studied by means of artificial simulation dust reduction and spectral measurement. The spectral absorption characteristics of iron elements and the dominant band with the best correlation between dust content and plant leaf spectra were used. Two quantitative inversion models of leaf dust amount based on dominant band reflectivity of plant leaves and unique spectral absorption index based on iron elements were established respectively. The results show that the difference between the spectral curve of plant leaf reflection and the spectral curve of dust decreases with the increase of dust content in iron tailings. There is a significant correlation between the dust content and the spectral variables of plant leaves in the two inversion methods, but the quantitative inversion model based on the absorption characteristics of iron elements is more accurate. The results can provide a basic model and technical basis for the application of hyperspectral remote sensing in quantitative monitoring of dust content in mining areas.
【作者单位】：东北大学测绘工程系;
【基金】：国家自然科学基金青年基金项目“铁矿区植被综合胁迫的全波段光谱特征及协同反演模型”(编号:41201359)资助
【分类号】：X87;X753

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