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  • ACRS 1998


    Oceanography/Meteorology
    Estimating Atmospheric Turbidity from SPOT and GMS-5 Data

    Methodology
    The method of AOD retrieval from satellite data developed by Tanre et al. in 1988 was improved by Liu et al. in 1997. The improvements of SF method contain : (1) The single- directional SF is replaced by multi-directional SF to describe the surface characteristics more completely 92) Introduce an "optimum number" to reduce the characteristics effects of local landcovers and terrain. Inthis study the improved algrithm of AOD retrieval is applied for the high spatial resolution SPOT data and hourly GMS-5 data. The flow chart of using satellite data to monitor the air pollution is showed in figure 1. In the flow chart, two points are very important : one is the AOD retrieval and the other is to establish the relationship between AOD and S.S. Basically, the relationship between AOD and turbidity or air quality index is more complex. The variation of surface boundary layer thickness and ground observation range seems to be unclear, and need more analysis to find the relationship between AOD and S.S. This research need to be studied continuously because it is practical in the air pollution monitoring in the future.


    Figure 1. The flow chart of using satellite data to monitor the air pollution.

    Results
    1.AOD retrieved from SPOT data
    Seven SPOT images, Mar. 7, Apr. 3, Jun. 28, Aug. 10, Aug. 31, Sep. 16, and Sep. 26 in 1994, are used to retrieve the AOD in this paper.The reference AOD is obtained by DDV method (Liu et. Al., 1996) for lack of ground measurements during the SPOT images observation. The results of AOD retrieval of 3 test area in each channel of SPOT are shown in table 1 and seems to be very reasonable when compared with the results of DDV method, especially for few or few or none DDV pixels in the images on 7 Mar and 26 Sep, 1994. The distribution of AOD retrieval from XSI data, 31 Aug, 1994, is shown in figure 2. The AOD on the right-down and left-down area of the figure are larger than other area because of one industrial area or some manufacture locations and a little urban.

    AOD of SPOT XSI
    DataDDV methodSF method
    Area1Area2Area3MeanStd
    1994/03/071.59580 .74165.75668.76108.75314.00823
    1994/04/03.65540.61667.62257.60847 .61590.00578
    1994/06/28.44530.52885.42064.45748 .46889.04779
    1994/08/10.40840(ref.).43395.43395.43395.433950
    1994/09/26.12990.57785.54803.42580 .5172306578
    1994/08/31.45690.58989.54566.50144 .54566.03611
    1994/09/19.43140.63786.56861.48750 .56466.06144
    AOD of SPOT XS2
    DataDDV method SF method
    Area1Area2Area3MeanStd
    1994/03/071.34590 .68829.71965.74514.71769.02325
    1994/04/03.55160.52445.55613.57545 .55201.02102
    1994/06/28.37270.47250.43114.36419 .44261.04462
    1994/08/10.53640(ref.).42779.42779.42779.427790
    1994/09/26.08430.42004.54969.38529 .45167.07075
    1994/08/31.37810.42274.51481.45723 .46493.03798
    1994/09/19.34020.43374.49018.37193 .43195.04829
    AOD of SPOT XS3
    DataDDV methodSF method
    Area1Area2 Area3Mean Std
    1994/03/071.03050.64990.65513.67113.65872.00903
    1994/04/03.42080.52758.44424.51858.49680.03735
    1994/06/28.28190(ref.).28543.28543.28543.285430
    1994/08/10.82270.45917.46117.48701 .46911.01268
    1994/09/26.04280.30467.27128.36234 .31276.03761
    1994/08/31.28100.47419.40316.46395 .44710.03135
    1994/09/19.23440.33094.32229.33291 .32871.00461
    Table 1. The comparison of AOD retrieved from SPOT data by SF and DDV methods.

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