Inversion Of Uranium And Associated Heavy Metal Contents Based On Leaf Reflectance Spectral Characteristics

With the increasing demand of national defense and nuclear power industry for uranium resources,a large number of uranium waste rocks and uranium tailings are inevitable in the process of uranium mining and utilization.The average uranium content of uranium tailing and surrounding contaminated soil is 4-10 times higher than the natural background value,and its surface radiation dose is 5-70 times higher than that of general soil.Uranium tailings have become a radioactive pollution source that can not be ignored.How to determine the radioactive and heavy metal pollution risk of uranium tailings and surrounding soil and repair them when necessary,study the correlation mechanism or mechanism between plant leaf reflectance spectrum and soil uranium and associated heavy metal content,especially explore how to use plant leaf reflectance spectrum to retrieve uranium and associated heavy metal content in soil and plant leaves,and finally realize the remote sensing method Large area and efficient monitoring of uranium and associated heavy metals pollution and remediation effect of uranium tailings and surrounding soil provides theoretical and technical innovation,which has become the key scientific problem proposed and interpreted in this dissertation.The author carried out five plants ramie(Boehmeria nivea),Indian mustard(Brassica juncea),sorrel(Rumex acetosa L.),rape(Brassica napus L.)and corn(Zea mays L.)pot experiment under different concentrations of uranium,cadmium and lead pollution.The characteristics of enrichment and tolerance of experimental plants were analyzed.The reflectance spectra of plants at different growth stages were measured.The reflectance spectra of leaves were analyzed according to spectral angle,sensitive wavelength and spectral characteristic parameters.Based on the reflectance spectra of leaves,the contents of heavy metals in soil were retrieved by statistical method.While the contents of heavy metals in leaves were retrieved by statistical method,vegetation index method and physical method,respectively.This dissertation reveals the quantitative relationship between leaf reflectance spectrum characteristics and uranium and associated heavy metals in soil and leaves,realizes direct and indirect inversion of uranium and associated heavy metals in soil,and explores the response mechanism of soil heavy metal pollution in leaf reflectance spectrum,which provides theoretical basis and technical support for monitoring the pollution degree and remediation effect of heavy metals by remote sensing.The main research results and innovations are as follows:(1)By measuring and analyzing the leaf reflectance spectra of 32 growing periods of experimental plants,it is found that the spectral angle,sensitive wavelength and spectral characteristic parameters of plants may change under the pollution of uranium,cadmium and lead.The spectral angle reflects the macroscopic variation of the spectrum,which can be directly used for the inversion of soil heavy metal content.In most of the experimental conditions,the spectral variation of leaves under heavy metal pollution was significant.The contents of heavy metals in soil were successfully retrieved from spectral angle in 16 growing periods.From the perspective of leaf scale remote sensing detection,rape can be regarded as an indicator plant of uranium,cadmium and lead pollution in soil.The spectral angle of Xiangzhu No.7 also indicated the pollution of uranium and lead in soil.According to the sensitive wavelength,spectral characteristic parameters,vegetation index and leaf radiation transfer model prospect based on spectral characteristics,the retrieval of heavy metal content in leaves was successfully achieved in all 32 growing periods when effective sprctral data were gathered.Judging from the relationship of heavy metal contents between leaf and soil,Indian mustard and rape can be used as index plants and monitors for uranium pollution,and rape can also be used as monitor for uranium,cadmium and lead in most growth periods.The regression equation of heavy metal content in soil and leaves showed that heavy metal content in leaves could reflect the content of heavy metals in soil.In other words,taking the leaf heavy metal content as the intermediary,the application range of soil heavy metal content retrieval from leaf reflectance spectrum characteristics was expanded.(2)Basically,the relationship between the reflectance and the original spectra was positive.The sensitive wavelengths of dicotyledons and monocotyledons were different,and the sensitive wavelengths of original spectra of experimental plants under different heavy metal pollution were significantly different,too,which mainly distributed around 370,600,770 and 980 nm.Compared with the original spectral sensitive wavelength,the first derivative spectrum is more sensitive to heavy metals.The results showed that the derivative values corresponding to the sensitive wavelengths of the first derivative spectra at different growth stages had the same correlation with the heavy metal content in leaves,which were mainly distributed around 380,550,800 and 950 nm.In general,the determination coefficient of the regression equation with the first derivative spectral sensitive wavelength as the independent variable is larger than that of the regression equation with the original spectral sensitive wavelength as the independent variable or the two are equal.(3)The results showed that the spectral characteristic parameters were significantly correlated with the heavy metal content in leaves of all the five plants and three heavy metal pollution accumulation periods,and the ratio parameter SDnir/SDre had the potential to be an ideal spectral characteristic parameter for monitoring heavy metal content.Comparing the inversion based on sensitive wavelength and spectral parameters from response time,determination coefficient and number of regression equations,the inversion based on spectral parameters is slightly better than that based on spectral parameters.It is proved that spectral parameters have integrated the characteristics of multiple sensitive wavelengths,which can avoid the contingency of a single band and have strong ability to extract information.(4)52 specific forms of vegetation index were determined for the retrieval of heavy metal content in leaves,and some parameters in the original form of vegetation index were replaced.Among them,RBRI3?PRI22?TVI3?CARI12 and MCARI2 were more suitable for heavy metal content inversion than the corresponding original forms.(5)The inversion of leaf structure parameter N in the radiative transfer model of leaf PROSPECT was carried out by using sensitive wavelength.Compared with N determined by two empirical formula,the correlation between N and heavy metals was greatly improved.The anatomical structure parameters of leaves were measured.It was found that under heavy metal pollution stress,the whole leaf thickness and epidermis thickness,lower epidermis thickness,epidermal cells,vascular bundles,palisade tissue,vesicular cells and other indicators changed significantly.N was calculated from the anatomical structure parameters of leaves,which provided a way to determine N.The regression equations of leaf structure parameters N and leaf anatomical structure parameters were obtained by multiple linear successive regression,and the physical method was used to retrieve the heavy metal content in leaves.(6)Due to the comprehensive selection of spectral characteristic parameters and vegetation index,the statistical method and vegetation index method are better than the physical method in terms of the number of growth periods retrieved successfully and the maximum determinant coefficient R2.The results of statistical inversion show that uranium enriched plants are more conducive to monitoring uranium content through their leaf spectra in the early growth stage,and the strong tolerance of plants is likely to have a negative effect on the inversion of uranium and associated heavy metal content in leaves,especially in the late growth stage.But according to the vegetation index method and physical method,the law is not obvious.On the whole,it is possible to obtain high quality regression equations for both enriched and non enriched plants.