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.
徐奥, 马保东, 李兴春, 吴立新. 植物叶面铁尾矿粉尘光谱测试与定量反演实验[J]. 国土资源遥感, 2017, 29(1): 164-169.
XU Ao, MA Baodong, LI Xingchun, WU Lixin. Spectral testing and quantitative inversion for dust of iron tailings on leaf. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(1): 164-169.
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2017, Vol. 29 
