This paper quantified regional concentration of various metals(e. g. Pb, Cu, As, Hg, Mo) in the leaves by developed regression equations based on Kokaly and Clark(1998) using Pushbroom Hyperspectral Imager (PHI) data which acquired at Daxin'anling area, Helongjiang Province, China. The regression equations were developed and established between metal concentration and spectral absorption band-depth of vegetation branches which both were measured in the field in study area. An iterative algorithm was used to select suitable wavebands from 80 bands corresponding to PHI band center wavelengths during the regression processing, which maximize R2 and minimize Std. Except Pb, the correlation coefficient(R2) of all the other metals are up to 0.8. These regression equations were applied to PHI data in order to estimate the regional metal concentration in close vegetation cover of study area after spectral reconstruction and absorption band-depth transformation of PHI data. The distribution tendency of concentration of various metals quantified from PHI data were in good agreement with the ground geochemical distribution.
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