Study Of Plants Spectrum Features And Information Extraction In Dexing Copper Mining Area

According to distribution of barren and waste land in Dexing copper mine, remote sensing biochemistry methods were applied in the research on some of predominant plants, including Rhus Chinensis Mill, Sweet Wormwood Herb, Comnyza Canadensis (L.) Cronq. , Mosla Chinensis Maxim and Dicranopteris pedata. Heavy metals' distributing pattern in soil-plant system at AMD contaminated land and tailings dam was analysed. Wavelet transformation was taken to estamate noise variance and denosing. Type of noise was made sure via theoretical analysis and emulational experiments. And spacially correlated filtration was chosen for field spectrum denoising. 44 indexes were employed to analyze the features of spectrum of these five plants. And heavy metals contained in leaves and its enrichment index were estimated by stepwise multianalytical regression model.The findings indicated that, total heavy metal concentration in acid mining drainage contaminated soil and in soil of the tailings storehouse was higher in the middle of storehouse than the top of dam, and showed the tendency as the river bed > the pollutes area > nearby the aqueduct of waste rock dam. Comparing with the soil geochemistry background value, the Zn, Mn, Cd, Ni, Pb, Cu content were higher than the their background value of the Chinese A-layer soil and A-layer laterite, especially Cu was far higher than its background value, while Cr is nearly equal to its background value. Comparing with the Chinese soil environmental quality standard value, the majority soils didn't satisfy the standards requests of the second levels of the national standard, but nearly all soils satisfy the standards requests of the third levels. These soils can just satisfy production of the farming and forestry industry and just can meet the need for plant growth, but cannot safeguard the agricultural production, and the human body health.The five gathered plants survived in the study area where the heavy metal content is very high in soils, and was obviously influenced by the soil heavy metal. The heavy metals mostly concentrates in the root, while concentrate in the leaf of partial plants. The plants displayed varous enrichment characteristic to the copper element. In the organs of Mosla Chinensis Maxim the heavy metal content is very high, and has obviously enrichment characteristic of copper. Research result pointed that, the first scale decomposed details could be well employed to estimate the noise variance and this method has high accuracy and stability. This estimation could be realized based on the spacially correlation algorithm. The noise mainly distributed in the first and the second wavelet decomposed scale, and the noise variance also changes along with the wavelength change.Noise is remarkable nearby 1400nm and 1900nm where the water absorption exists. The emulational experiments and the theoretical analysis indicated that, the noise in the field vegetation spectrum belongs to be dividing noise, and the logarithm transformation and wavelet transformation can make it white. In three kind of wavelets noise reduction method, the spacially correlation filtration most suits to field vegetation spectral data processing, the next is the module maximum filtration. The threshold shrinking method is not suitable to spectral data noise reduction. The improved self-adapted spacially correlation filtration is suitable for spectral data processing. This method may effectively reduce the noise in the bands from 350nm to 2500nm, including bands nearby 1400nm where water absorption exists.But the noise nearby 1900nm cannot be effectively removed. The reason possibly lies in the precision insufficiency of the spectrum instrument system.The spectrum feature findings pointed out that, major spectrum indexes of the five kind of plants is remarkable different along with environmental variation. Linear relevance of spectrum indexes and heavy metal content in the leaf is various. An common rule is: The heavy metal effect often displayed as it changed plant's moisture content, the pigment content, the leaf structure, and so on, promoting or counteract the water absorption. Some heavy metals hinder the pigment synthesis, but Zn can promote it. Some of the heavy metals may destroy the leaf structure and causes the higher valuesof the infrared indexes of reflection spectrum. One kind of heavy metal effect often has many response features in reflection spectrum. Different heavy metals like Pb, Zn, has the varying degree in the identical feature of the reflection spectrum, for instance in water absorption band. The reason lies in that the heavy metal in plant often combined with the protein, and acted as the biocatalyst, the enzyme, and participated in the different biochemistry process. But the biology also has certain limit of the demand of the essential heavy metals i.e. Zn. When essential heavy metal content achieved certain degree in the growth matrix, the poisoned effect presented. But this kind of poisoned effect influence on certain body functions but not on all of them. Regarding biological non-essential element like Pb, when the poisoned effect presented, many biological functions like water absorption, the pigment synthesis, and so on, were affected and could not be normmally carried on, thus it caused many spectral response. But between the different plant there were also some differences, it maybe owned to the different species ability of the heavy metal absorpting, concentrating and tolerating.The research on leaf heavy metal content and its enrichment indexes proved that, Stepwise multianalytical Regression model can be found. The model predicted value and the actual value comparison showed that the model is stable, and the relative deviation mostly below±10%. The first order and the second differential spectrum was employed to estamate the heavy metals contained in the leaves and their enrichment indexes for Sweet Wormwood Herb, Comnyza Canadensis (L.) Cronq. and Mosla Chinensis Maxim. The findings indicated that, except Pb and Mn, the differential spectrum model has good estimating effect, the relative deviation mostly is lower than 15%. The firstorder differential model and the second differential model has the difference on estamation of various heavy metal. The first order differential spectrum model can well estamate Cu and Ni in the leaves, while the second differential spectrum model can well estamate the Cr, Mn, Pb, Cd and Zn. The differential spectrum model can only well estimate the enrichment coefficient of Mn. As relative deviations of estimation on enrichment indexes of Cu, Cr, Ni, Pb, Cd and Zn are too high, the model can not be use to estimate the enrichment coefficients of these heavy metals. It looks forward for further studies and discussion.