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The Research Of Phytoplankton Biomass Of Ebinur Lake Based On Rs Technology

Posted on:2011-08-25Degree:MasterType:Thesis
Country:ChinaCandidate:S TangFull Text:PDF
GTID:2190330338975124Subject:Cartography and Geographic Information System
Abstract/Summary:PDF Full Text Request
Using RS and GIS to estimate Lake Phytoplankton biomass in arid area is rapid, accurate, large-scale, no damage, etc., which provides a strong basis for water quality parameters and plankton information. It is also very significant to research the lake eco-environment in arid area.This paper takes Ebinur Lake as the research object. Combining with measured spectral data, it uses CBERS-2, Landsat-7 ETM+ and ASTER images to obtain Ebinur lake water spectral characteristics. In order to establish the linear and nonlinear regression models which are significant correlation between phytoplankton biomass and remote sensing factors, the correlation between remote sensing of various factors and phytoplankton biomass is analyzed. The optimal model that is used to inverse Ebinur Lake phytoplankton biomass is selected by result comparison and residual analysis, and using it to make biomass production map which is used to analyze the distribution of phytoplankton biomass in Ebinur Lake. Conclusions are as follow:(1)Ebinur water bodies'spectrum curve had a rising trend in the blue band, in the green band it get peaks and then dropped sharply. In the red band it changed a little, and decreased significantly in the near-infrared bands.(2)Comparing with ETM, ASTER image through the measured spectral data and correlation analysis, CBERS-2 image was the most suitable for this study.(3)Five remote sensing factors that showed significant correlation were selected by analyzing correlation between measured biomass and value which came from the gray value of CBERS-2 band and calculation value in CBERS-2 band. Then this paper established linear regression model, curve regression model, multiple linear regression model which used remote sensing factor as the independent variable and measured biomass as the dependent variable. The optimal estimation model of Ebinur phytoplankton biomass was selected by comparing residual analysis and result. It was Y = 3.819-0.027 (G-B) -0.04 (G-R), and the degree of fitting was 0.832 and average residual coefficient was 6.9% respectively.(4)The total Ebinur Lake phytoplankton biomass was estimated as 9.95×10~5 kg by the use of water depth DTM and the biomass DTM.(5)According to Ebinur Lake phytoplankton biomass map, the general characteristics of Ebinur phytoplankton biomass were as follow. Ebinur Lake phytoplankton biomass in the overall trend was east with higher biomass and the west with lower biomass. It gradually decreased from the center of lake to lakeside like concentric circles, and southeast of lake had the highest biomass. The average biomass per unit area was 0-2.55mg / L, the average value was 1.1 mg / L.(6)Based on analyzing the phytoplankton biomass DTM section, this paper obtained the characteristic of Ebinur lake horizontal and vertical section biomass.
Keywords/Search Tags:Ebinur Lake, Remote Sensing Inversion, Phytoplankton Biomass, CBERS-2
PDF Full Text Request
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