Full
Outline
There is a serious problem of heavy metal compound pollution in lead-zinc mining areas. Hyperspectral remote sensing technology can be used to extract heavy metals absorption characteristic spectra from soil spectral information and achieve inversion of heavy metal contents in the soil of mining areas. Based on hyperspectral data, the heavy metals contents in soil, such as Cd, Pb, As and Hg, were retrieved from the soil of the Silongduo lead-zinc mining area in Xizang. The hyperspectral data from soil samples was collected and various spectral transformations were performed, including first differential (FD), second differential (SD), logarithm of the reciprocal (AT), first differential of logarithm of the reciprocal (AFD), and second differential of logarithm of the reciprocal (ASD). The characteristic bands that are strongly correlated with the measured content of heavy metal were selected and finally four inversion models were established, including stepwise multiple linear regression (SMLR), support vector machine (SVM), artificial neural network (ANN), and random forest (RF). The coefficient of determination(R2)and root mean square error (RMSE) were selected to evaluate the accuracy of the models and the optimal inversion model for each heavy metal was obtained. The research results show that the dimensionality reduction effect and feature band selection interval of different spectral transformation methods are different. Among the five transformations, SD transformation has the best effect and can effectively distinguish feature bands, followed by ASD and AFD transformations. The RF model has the best inversion effect, with a better applicability and inversion accuracy than SMLR, ANN, and SVM. The best inversion model for As is the AT-RF model, the best inversion model for Cd is the SD-RF model, the best inversion model for Pb is the ASD-RF model, and the best inversion model for Hg is the ASD-SMLR model. The average assessment values of Cd, Pb, As, Hg content models of soil exceeded the background value of Xizang soil by 124.2, 89.8, 0.70, 1.24 times, indicating that Cd and Pb were the main pollution factors of the soil in the mine concentration area, accompanied by the combined pollution of As and Hg.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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