| Aerosol play an important role in the atmospheric Environment.It not only affects the balance of the earth atmosphere system,but also is the key factor of urban a ir pollution.Aerosol optical depth(AOD)is the basic parameter of aerosol concentrati on,which can be used to calculate aerosol content and reflect the degree of atmospheri c pollution.The atmospheric aerosol data obtained by satellite remote sensing can compensate for unable to obtain the spatial distribution of atmospheric aerosol optical depth with high coverage rates in continuous time due to the scarcity of ground monitoring stations.The spatial differentiation characteristics of aerosol optical depth and its relationship with land use,elevation and population were studied,it can be of some practical significance to monitor the level of regional air pollutants and control air pollution pertinently.Central Plains Economic Region is one of the regions with the highest degree of economic,population and resource aggregation in central china,and the problem of air pollution is becoming more and more serious.This study first uses MODIS-Terra10 KM aerosol optical depths(MOD04 L2),extract aerosol optical depth of CentralChina city group in 2016,and analyze the temporal and spatial distribution characteristics of the region AOD.The 8 OLI remote sensing images,DEM images,GPW population raster data,Secondly by using The 8 OLI remote sensing images,DEM images,GPW population raster data.Finally,the degree of correlation between the factors and AOD was studied by means of Pearson Correlation andRegression Model.The main results of this paper are as follows:(1)The distribution of AOD of Zhongyuan Urban Agglomeration in 2016 is high in eastern China and low in western China.The AOD value of the eastern hilly region is generally higher than that of the western plain,The highest values are mainly distributed in the northeast of the study area,northern Zhengzhou,southern Jiaozuo,central Xinxiang and other built-up areas,The range of AOD value distribution is0.75~0.96,The range of AOD numerical range over Kaifeng,eastern Xinxiang,western Heze,southern Puyang and Anyang city,Xuchang built-up area,Zhoukou built-up area,Luoyang built-up area is 0.57~0.75.The range of AOD numerical range over southeast region of Pingdingshan,Luohe,Zhoukou,Zhumadian,Xuchang and the northwestern part of Yuncheng except its built-up area is 0.43~0.57.The AOD values in the Western Hills and mountains of the study area were 0.15~0.32 and0.32~0.43,respectively.(2)The seasonal variation of AOD in Zhongyuan urban agglomeration is obvious,The AOD concentration was highest in spring,higher in summer and autumn,and lowest in winter.The average value of AOD in the study area was obvious seasonal trend :spring> autumn> summer> winter,and the average value of AOD was 0.625>0.461>0.456>0.321.(3)Based on the analysis of the correlation between the average value of AOD and the ratio of the area of construction land in different time periods(annual,quarterly,monthly),All showed positive correlation at the confidence level of0.01,Most of the Pearson correlation coefficients are between 0.4 and 0.5which shows a significant correlation,The correlation coefficient of part of months are between 0and 0.3 which shows a relatively weak correlation.On the basis of the regression model between the average value of AOD and the occupation ratio of the construction land area in different time range,it is found that the best fit regression model is power function.(4)Based on the correlation analysis between the average value of AOD and the occupied area of the construction land in different intervals,it is found that the influence degree of the proportion of construction land area in different interval on AOD is different.The influence of the proportion of construction land area in different periods in different seasons on the AOD is different.The proportion of construction land area is between 1.03%-3.05%is the most obvious impact on AOD,and the second is between 1.03%-3.05%.(5)Based on the analysis of the correlation between the mean value of AOD and the digital elevation in different time ranges(annual,quarterly,monthly),the confidence level of the 0.01 showed a negative correlation,The vast majority ofPearson correlation coefficients are mostly between-0.5 and-0.8,showing a significant correlation,Only in summer,July,August,October,the Pearson correlation coefficient between AOD mean value and stem length are-0.227**-0.498**,-0.398**,-0.412**respectively,which showed a significant correlation.The optimal fitting function of the four seasons and January,May,September,December is power function,the optimal fitting function of February and March is logarithmic function,the optimal fitting function of June,July,August,October,and November is exponential function,The optimal fitting function of April is polynomial function.(6)Based on the correlation analysis between the average value of AOD and population density in different intervals(annual,quarterly,monthly),the confidence level of the 0.01 showed a positive correlation,the Pearson correlation coefficient between the average value of AOD and height were 0.333**,0.321**,0.315**,0.350**,0.337**,0.302**,0.300** in the whole year,spring,autumn,April,June,September,November,showing a significant correlation,the Pearson correlation coefficient between the average value of AOD and height were 0.297**、0.270**、0.268**、0.191**、0.286**、0.292**、0.242**、0.173**、0.257**、0.234** respectively in Summer,winter,January,February March,May,July,August,October,and December,showing a relatively weak correlation.The regression model between AOD average value and population density in different time range shows that the optimal fitting function is power function. |
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