| The optical properties of inland waters are affected by chlorophyll a(Chl-a),total suspended matter(TSM)and colored dissolved organic matter(CDOM),and their optical properties are very complex.TSM,as one of the water quality parameters,its content can reflect the degree of water pollution to a large extent,so it is an important indicator of water environment monitoring.Satellite remote sensing is an important technology for obtaining surface information over a long period of time and on a large scale,and it plays an important role in water environment monitoring.The lakes and reservoirs in Northeast China were the research object in this article.Based on the analysis of the optical characteristics of waters in Northeast China,this study explored different retrieval methods for TSM using remote sensing.According to the long-term TSM retrieval results,the changing characteristics on temporal and spatial were analyzed,and the natural and human activity factors that affect the spatial distribution and inter-annual changes of TSM were quantitatively analyzed.This article mainly achieved the following research results:1.Based on Landsat remote sensing reflectance data in this article,500m×500m grid points were used for uniform spectral sampling,and the optical characteristics of waters in Northeast China were comprehensively analyzed using their spectral characteristics.The fuzzy k-means method is used to perform spectral clustering and the results showed that the study area had three typical optical water types,which is of great significance for the remote sensing of TSS in the study area.2.Three methods were explored for TSM retrieval: retrieving using a unified model for the entire study area,retrieving based on different water optical types models,and weighting of different optical types models.The analysis results of different inversion methods with Landsat data showed that: for the first method,the exponential function model based on the mean value of the red and green bands((Red+Green)/2)was more suitable;For the second method,the retrieval result of the exponential function model based on the difference of red band and blue band(Red-Blue)was more reliable for Type 1 water,the exponential function model based on the green band(Green)is more suitable for type 2 water,and the quadratic polynomial model based on the red band is more suitable for type 3 water;for the third method,the retrieval results from the models of these three types waters are weighted fusion.3.Based on long-term Landsat images covering the study area,using the method that weighting of different optical types models,and through establishing a specific retrieving process,the time series of TSM in the study area from 1984 to 2019 are obtained.The results of the interannual change of the long-term TSM showed that the TSM changing trend in the study area tends to be good overall,most of them showed a decrease trend,but a few waters showed a significant increase trend;the change rates of TSM were mainly concentrated between-50% and 0,5% of waters had a TSM rising rate greater than 100%,which requires special attention;4% of waters had a higher overall TSM level(greater than 100 mg/L),which were focus in management.The analysis of the spatial heterogeneity of TSM showed that there was spatial heterogeneity in the distribution of TSM in waters,and the variability of TSM in some waters was significant;the spatial heterogeneity of TSM in waters also showed dynamic changes,but in general,The TSM in most waters tended to be homogenized,while in a few waters tended to be heterogeneity.4.Spearman correlation analysis and GLM analysis were used to quantitatively analyze the influencing factors of total suspended matter concentration in the study area by calculating the correlation coefficient and relative contribution.The results show that the spatial distribution and inter-annual variation of total suspended matter concentration in the study area are determined by known and unknown natural and human activity factors.The correlation analysis between the factors and the inter-annual variation of total suspended matter showed that: The influencing factors of significant correlation varied from basin to basin.NDVI and precipitation had a relatively small significant influence range,which were significantly correlated with the inter-annual variation of total suspended matter in 5 basins,respectively.Wind speed and fertilizer use had a wide significant influence range,which were significantly correlated with the inter-annual variation of total suspended matter in 13 and 14 basins,respectively.The relative contribution analysis of the factors to the inter-annual variation of total suspended matter showed that the total contribution of the 8 factors was between 14%and 75.4%,with an average value of 40.8%.The total contribution of the 8 factors was greater than 50% in the 10 basins.In terms of specific factors,the average relative contribution of population and DNVI was higher than that of other factors,which were7.9% and 7.6%,respectively.The minimum relative contribution of air temperature was2.1%.The regional difference of relative contribution of wind speed was the smallest(CV=0.84),and the regional difference of relative contribution of chemical fertilizer usage was the largest(CV=1.91).The average total contribution of the four natural factors was 19.9%.The average total contribution of the four human activity factors was 20.9%.The analysis of the influence of various factors on the spatial distribution of TSS showed that wind speed and precipitation were significantly correlated with spatial distribution of TSS(P <0.05).Compared with the other 7 factors,the relative contribution of wind speed was 23.4%.Other potential factors played a leading role,with a relative contribution of 69.9%. |
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