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Research On The Spectral And Photosynthetic Characteristics Of Landscape Plants Under Dust Pollution

Posted on:2014-06-11Degree:MasterType:Thesis
Country:ChinaCandidate:H L XiaoFull Text:PDF
GTID:2250330401968388Subject:Garden Plants and Ornamental Horticulture
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Dust pollution is one of zhe major factor resulting environmental pollution in cities, endangering people’s health. Landscape plants can effectively reduce the dust content in the air and landscaping is an important method for improving the urban environment. In this study, we explored the dust pollution effecting on the spectral and photosynthetic characteristics of the landscape plants, which respectively planted in the severe pollution area Wugang coking plant (’Wugang’), the general pollution area Qingshan peace park (’Qingshan’) and the control area Huazhong agriclutre university (’Huanong’), through researching the dust-retention content and the photoresponse and spectral reflectivity of plants, and we established the inversion models between the content of dust-retention and spectral characteristics in order to provide a reasonable basis and practical application for using the spectral characteristics to survey the dust-retention content. The research results are shown here:(1) We measured and compared the content of dust-retention per unit area and per single leaf of landscape plants in the different pollution areas and found them were significant differential in the different landscape plants. The content of dust-retention per single leaf of the Huanong is ranged in0.126mg~13.526mg, and the content of dust-retention per unit area is ranged in0.002mg/cm2~0.099mg/cm2, the average content of dust-retention per unit area is0.041mg/cm2; the content of dust-retention per single leaf of the Qingshan is ranged in0.423mg~34.350mg, and the content of dust-retention per unit area is ranged in0.035mg/cm2~0.258mg/cm2, the average content of dust-retention per unit area is0.075mg/cm2; the content of dust-retention per single leaf of the Wugang is ranged in0.852mg~138.592mg, and the content of dust-retention per unit area is ranged in0.035mg/cm2~0.258mg/cm2, the average content of dust-retention per unit area is0.274mg/cm2. In the present study, a changeing tendency of the content of dust-retention per unit area of the same species landscape plant at different sampling sites showed as the Wugang> Qingshan> Huanong, and this tendency was consistent with the results of the three test sites atmospheric pollution, it fully proved that the dust detaining content of plant could indirectly reflect the pollution of local environment at some extent.(2) In this study, the data of light response of the landscape plants was fitted using a non-rectangular hyperbolic model, and the coefficient of determination R2>0.950in all plants of the three experiment sites, the result showed that the non-rectangular hyperbolic model could fitted the light response curve well. According to the analysis of the characteristic parameters of light response curve of the landscape plants under different dust pollution environment, the results showed that the maximum net photosynthetic rate (Amax) of83%of the sample plants clearly presented a tendency as the Huanong> the Qingshan>the Wugang; more than66%of the samples have the maximum value of the apparent quantum efficiency (AQE) at Huanong and more than50%have the minimum value of the AQE at the coking plan; in addition, more than66%of the samples have the maximum value of the light saturation point (LSP) at Huanong and more than58%have the minimun value of the LSP at the Wugang. Thus, the parameters of the light response curve of the landscape plants in different dust pollution environments presented a decreasing tendency with increased levels of dust pollution in the environment, indicating that the photosynthesis of the landscape plant were significantly affected by the external environment dust pollution and the dust pollution directly affected the photosynthesis light response characteristics of plant.(3) Based on the spectral absorption characteristics and the spectral red edge characteristics, we extracted nine reflectance spectra characteristic values of the landscape plants. In the present study, we found that with the increase of the levels of dust pollution, the green peak reflectivity, the maximum absorption depth of the red valley and the red edge amplitude were all have a decreasing trend, however, the red valley reflectivity had a increase trend. In addition,83%of the total measured samples occurred redshift at the position of the green peak and the red valley. These results suggest that the selected characteristic parameters have a certain correlation with the environmental dust pollution, and the atmospheric dust pollution has a significant effect on the spectral reflectance of the landscape plants. (4) This paper observed that building a simple regression model with the spectral characteristics and the content of dust-retention per unit leaf area was not good (R2<0.3); another multiple linear stepwise regression model was builded with the merged reflectance spectra data of the arbor, the shrub and the grass with the content of dust-retention per unit leaf area, and the result was also not good (R2<0.6); But, building multiple linear stepwise regression models with the reflectance spectra data of arbor and that of shrubs and grass, respectively, with the content of dust-retention per unit leaf area was better than previous two methods, the R2was significantly increased, the R2of the inversion models of the first derivative of the shrub and the first derivative of the arbor were0.928and0.896, respectively, and we suggest that these two optimal models, Y=0.347-0.538X1-0.316X2+0.959X3-2.713X4+4.798X5-2.988X6+6.218X7and Y=0.219+0.236X1-0.257X2-0.248X3-0.383X4+2.754X5+1.710X6-0.185X7, can be used for inverting the dust-retention content of the shrub and grass and the arbor by the hyperspectral, respectively.
Keywords/Search Tags:Landscape plants, Dust-pollution, Photosynthetic characteristics, Spectrumcharacteristics, Dust-retention capability, Estimation model
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