Zhexiu Yu, Chao Zhang, Wei Ren, Yi Zhang, Xiaohua Niu, Yan Wang, Yungen Liu. Study on Estimation Model for Arsenic Content of Typha orientalis by Hyperspectral Data[J]. Journal of Southwest Forestry University, 2020, 40(6): 87-96. DOI: 10.11929/j.swfu.201902049
Citation: Zhexiu Yu, Chao Zhang, Wei Ren, Yi Zhang, Xiaohua Niu, Yan Wang, Yungen Liu. Study on Estimation Model for Arsenic Content of Typha orientalis by Hyperspectral Data[J]. Journal of Southwest Forestry University, 2020, 40(6): 87-96. DOI: 10.11929/j.swfu.201902049

Study on Estimation Model for Arsenic Content of Typha orientalis by Hyperspectral Data

  • Typha orientalis as a typical wetland plant were cultured in different arsenic concentration gradients. The reflectance spectrum data of T. orientalis were collected, and the reflectance spectrum characteristics of T. orientalis under different arsenic concentration were analyzed. Estimation models were established by original spectral reflectance, derivative spectrum and narrow band vegetation index. The result showed that the reflectance features of T. orientalis in different gradients was similar to that of healthy green vegetation, but the reflectance of the 8th and 9th gradients were lower than that of other gradients in the band range of 1950-2450 nm. The obvious difference of near-infrared band range between different arsenic gradients after first order derivative and second order derivative transformation. Reflectance spectral difference were analyzed quantitatively by ratio variables of 'three edges' parameters between different arsenic gradients. The correlation was negative between the original spectral reflectance and arsenic content. The highest correlation between the second order derivative reflectance of 973 nm and arsenic contents, the correlation coefficient was −0.494. The highest correlation index combination was FRVI (1065, 1260) in all narrow band vegetation indices, the correlation coefficient was 0.760. The best regression model was based on FRVI (1065, 1260) in all models, R2 and RMSE were 0.793, 107.457 respectively.
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