Research For Cd Stress Of Rice Based On Hyperspectral Remote Sensing

Farmland of heavy metal pollution has drawn wide attention, which is the worst serious environmental problems we are facing. The heavy metal pollution has characteristic of complex confidentiality, durable harm, especially may endanger our human health enrich through the food chain. Therefore, it's very urgent to monitor a large area of farmland quickly and accurately, it also has important academic value and practice significance.This study based on 863 project, study on remote sensing weak information recognition and extraction through heavy metal density of small changes in wide range. Based on outdoor test and hyperspectral image data(Hyperion) this research established rice cadmium pollution stress level appraisal model, providing theoretical foundation and scientific basis for big range fast and non-destructive monitoring rice cadmium pollution, with strong theoretical and realistic significance.The ground remote sensing methods use ASD FieldSpec spectrum analyzer to obtain the rice canopy spectral data. The variation of physiological characteristic parameters in Cd -induced stress on rice is complex and unobvious, which lead to subtle changes in spectral curve shape. Some methods were used to enhance and extract subtle spectral feature information associated with heavy metal pollution. Hyperspectral data of rice canopy and biochemical parameters were measured. Three methods were used, namely principal component analysis (PCA), independent component analysis (ICA),wavelet transform fractal analysis. Spectral parameters sensitive to Cd contamination, namely F1, ICA1 and fractal dimension of spectral reflectance (D), were obtained by different methods. The above sensitive factors were used to establish one-dimensional diagnosis model for rice under Cd contamination with satisfactory results. The correlation coefficient (R2) between three sensitive spectral parameters and Cd concentration were above 0.8. In addition, stable, sensitive and visual diagnostic methods were achieved by two-dimensional and three-dimensional diagnostic models with three diagnostic indicators. Multi-dimensional spectral diagnostic models can provide an effective way to monitor rice under Cd Stress comprehensively, systematically on a large scale. Hyperion hyperspectral data were used to establish a diagnosis model. Firstly convert the DN value to the surface real reflection. Wavelet function has been used to decomposite image spectrum of the experimental area. The results showed that the 3th layer of the db5 wavelet's to the signal decomposition spectrum fractal dimension with the most stable and reliable. And with Changchun region two cadmium pollution levels of different areas, for example, Hyperion image wavelet decomposition obtain details of fractal graph spectra signals big scope, identification of rice cadmium pollution degree. Intimidation, study on the case of Changchun's two regions of different levels of cadmium contamination, achieved the image of Hyperion detail signal wavelet decomposition, and obtained spectra of fractal graph, distinguished big range of rice cadmium pollution degree. This method provides a convenient way for monitoring rice cadmium pollution quickly, accurately and in a large scale.