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The Study On Optical Properties And Remote Monitor Of Black Water Blooms

Posted on:2018-09-13Degree:MasterType:Thesis
Country:ChinaCandidate:S M ZhangFull Text:PDF
GTID:2321330518990102Subject:Geographical environment remote sensing
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The black water blooms is an extreme manifestation of the eutrophication of the water body. It is a dark brown water body formed after the death of the algae in the eutrophic lake. The occurrence of the black water blooms leads to the rapid deterioration of the water quality and the serious damage to the ecosystem. At present,the monitoring of the black water blooms mainly relies on manual inspection, it is difficult to grasp space distribution of the black water blooms in whole lake. During the formation of the black water blooms, the change of composition and concentration of water body, resulting in the water color of the water has changed, which is received by the remote sensing sensor and become the physical basis for the application of remote sensing technology to monitor the occurrence and development of the black water blooms. In this paper, Taihu Lake as the research object, to carry out indoor simulation of black water blooms formation and field observation of black water blooms, analysis the optical characteristics of black water blooms. Based on the multi-spectral data of environment-1 satellite, the band-band ratio algorithm model and the maximum algorithm peak height algorithm model are used to extract the black water blooms. The research results can provide data support for water environment supervision. The main conclusions are as follows:(1) Optical properties of black water bodiesThrough the indoor simulation experiments can be seen, many cyanobacteria particles can form black water blooms after death degradation in the appropriate temperature conditions. During the process of indoor simulated black water blooms formation, the concentration of dissolved oxygen (DO), Eh and chlorophyll showing a downward trend. The absorption coefficient of CDOM is increasing and has a good correlation with chlorophyll a in the process of formation of black water bloom, and the absorption coefficient of non-pigment particles showing a downward trend. The phenomenon of black water blooms in the field of Taihu Lake also has the characteristics of high chlorophyll a and CDOM concentration. The proportion of auxiliary pigments in the black water blooms is low, mainly dominated by chlorophyll a, and the absorption coefficient of CDOM has a good correlation with chlorophyll a,which proves that CDOM is mostly derived from the degradation of cyanobacteria.Compared with the normal water bodies in the Taihu Lake, the reflectance spectras of black water blooms are very low in the range of 450-660nm, which led to the perception of these water areas as "black".(2) Analysis of influence of water components on reflectance spectras of black water bloomsThe parameters such as ag (440nm), chlorophyll a concentration and inorganic suspension concentration used in Hydrolight model were obtained from indoor simulation experiment sampling, and the remote sensing reflectance and backscattering were simulated under the corresponding parameters. The process of remote sensing reflectance and backscattering showing a downward trend during the formation of black water blooms by Hydrolight. We focus on water optical character variation during black blooms and analysis the main factors which contributes to "black" based on in field measurement and laboratory experiment. When the concentration of inorganic suspended matter is increasing, the value of remote sensing reflectance is increasing,but with the increasing of ag (440nm) and chlorophyll a concentration, the value of remote reflectance spectra is decreasing in the visible range, and the presence of CDOM concentration and chlorophyll a concentration in the visible range will decrease the reflectivity of the inorganic suspension. Compared with the experimental data of the black water blooms in the field, the contribution of the absorption coefficient of the pigment particles to the total absorption in the black water blooms is dominant, and the contribution of the CDOM to the total absorption is higher than that absorption coefficient of pigment particles. The contribution rate of CDOM to total absorption coefficient during the formation of black water blooms is increasing.In the black water blooms, the high concentrations of CDOM and chlorophyll cause a strong absorption of water in the visible range, low concentration of inorganic suspended causes a low backscattering, which make the black water blooms have low reflectance spectra. The results show that the sensitive water quality parameters of the black water blooms are CDOM and chlorophyll-a concentration.(3) Remote sensing monitoring of black water blooms based on HJ-1 satelliteThe study of the optical properties of black water blooms during the formation of the black water blooms in laboratory experiment and field measurement. By analyzing the optical properties of the black water blooms in the satellite image,we can see that the black water blooms have a low reflectance value in the first three bands and a very low reflection peak at the band 2. The spatials of black water blooms were extracted by the band ratio Band 2 / Band 1, band ratio normalization (b2-bl) / (bl+b2), the highest fluorescence peak height (MPH (560nm)) algorithm model. The three kinds of algorithm models were applied to HJ-1 multispectral image data from 2009 to 2015 year which has record the occurrence of the black water blooms. By comparing the results of the algorithm with the visual interpretation results, the highest fluorescence peak algorithm is the most accurate and less affected by the atmospheric correction.The applicability of the Band 2 / Band 1 algorithm is higher than the band ratio (b2-b1)/ (bl-b2), but the threshold range of the band ratio band 2 / Band 1 algorithm fluctuates greatly, and the band ratio normalization (b2-b1) / (b1+b2) is easy to divide the dark pixels in the river for the black water blooms.
Keywords/Search Tags:Black water blooms, Taihu Lake, Optical characteristics, Remote sensing monitoring, Algorithm model
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