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  • ACRS 1999


    Environment
    Applying SPOT Data to Estimate the Atmospheric Aerosol Optical in Complex Terrain

    3. Data
    This study used multi-temporal SPOT images to estimate the atmospheric aerosol optical depth. The data set includes 6 SPOT imageries acquired between April to August, 1998 covering Chung-Li area. The geometric information of the data set is shown in Table 1. meanwhile, the sun photometer data were collected at the same time. The aerosol depths derived from sun photometer data were used to verify the accuracy of the method proposed in this study ( Table 2).

    DateLoc View AngleSolar Angle
    al timeZenith AzimuthZenith Azimuth
    1998/04/2402:23-2919324117
    1998/05/1102:27-2319320107
    1998/06/2702:24-301932189
    1998/07/0202:28-24 1932090
    1998/07/3002:593119315110
    1998/08/2102:36-919322119
    Table 1.The geometric information of SPOT images used in this study


    Date1020nm 870nm670nm440nm
    1998/04/240.1330.1570.2490.470
    1998/05/110.2720.3260.4990.860
    1998/06/270.1250.1410.2150.418
    1998/07/020.0880.0920.1510.296
    1998/07/300.1590.1750.2590.478
    1998/08/210.0500.0380.0590.105
    Table 2. Aerosol optical depth collected by sun photometer.

    4. Result and Analysis
    The singular structure function pattern are depicted in the Figure 2(a) . as mentioned previously, these poor structure functions are mainly caused by satellite observation geometry and complex land cover distribution. Therese patterns would induce further errors in the optical depth estimation. When multi-directional structure function is employed as illustrated in Fig 2(b), the improvement is evident.




    Figure 2(a) The varieties of the structure function with different distances of SPOT XS1 Channel .(b) same as (a), except for multi-directional structure function.

    Further analysis showed the some abnormal patterns still existed in our approach. Therefore, the " optimal number " decision was added to determine the proper distance value, d and made sure that the abnormal structure function patterns can be removed.

    The final result is summarized in Table 3. obviously, the accuracy of multi-directional method is better than the single-directional method, except on may 11 ( party cloudy ). The error is reduced from 33% to 9%. The result reveals improvement in accuracy derived from multi-directional method and the optimal number decision .

    DateSunphotometer measurementsSingle-directionalMulti-directional
    RetrievedError (%)RetrievedError (%)
    1998/04/240.3390.386140.3483
    1998/05/110.6470.394390.37443
    1998/06/270.2990.347160.3114
    1998/07/020.2090.277330.2289
    1998/07/300.3150.356130.3459
    1998/08/21*0.078 ------------------------
    Table 3. The comparison between the estimated optical depths estimated by the single & multi direction structure function methods .( *: reference date )

    5. Conclusions
    The results strongly suggest that including multi-direction and optimal number in structure function method will greatly improve the accuracy of derived aerosol optical depth. In the further study, the relationship of test area size and distance values are necessary to be investigate in detail. In order to verify the accuracy of optical depth estimation, the accuracy and method of deriving optical depth from sun photometer observation is also an important task.

    Acknowledgements
    This work has been supported by grant form the National Science Council, China Taipei under NSC86-2612-E-008-007.

    References
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    • Griggs M., 1975: Measurements of atmospheric optical thickness over water using ERTS-1 data . Journal Air Pollution Control Association. 25, 622-626.
    • Holben B.N., Y.J. Kaufman, A. Setzer, D. Tenre', and D.E. Ward, 1990: Optical properties of aerosols from biomass burring in the tropics, BASE-A, Presented at e Chapman Conference on Biomass Burning. Williamsburg, VA, Mar., 1990.
    • Holben B.N., E. Vermot , Y.j. Kaufman, D. Tenre, and V. Kalb, 1992: Aerosol retrieval over land form AVHRR data application for atmospheric correction. IEEE Trans. On Geoscience and Remote sensing, 30(2), pp.212-222.
    • Kaufman Y.J., R.S. Fraser, and R.A. Ferrare, 1990: Satellite measurements of large -scale air pollution methods. J. Geophys, Res., 95(D7), 9895-9909.
    • Liu C.H, A.J. Chen, and G.R. Liu, 1996: An image-based retrieval algorithm of aerosol characteristics and surface reflectance for satellite images. INT. J. Remote sensing , 17(17), 3477-3500.
    • Liu G.R, T.H. Lin ,a dn A.J. Chen , 1997: An improved method to determine aerosol optical depth from SPOT data. COAA ' 97-First international Ocean -Atmosphere Conference, 18-19 Oct 1997, Washington , D.C., USA.
    • Mekler Y.,H . Quenzel, G. Ohring, and I. Marcus, 1977; Relative atmospheric Aerosol content from ERTS observation .J. Geophys. Res., 82, 9868-972.
    • Rao C.R.N., E.P. McClain, and C.C. Stowe, 1989: Remote sensing ofg aerosols over the oceans using AVHRR data theory. Practice and Application, INT.J. Remote Sensing , 10 (4-5), 743-749.
    • Sifakis N.I., N.A.Soulkellis, and D.K. Paronis, 1998: Quantitative mapping of air pollution density using earth observations : a new processing method and application to an urban area. INT . J. Remote sensing , 19(17), 3289-3300.
    • Tanre D., C. Devaux, M. Herman, R.Santer, and J.Y. Gac, 1988: Radiative properties of desert aerosols by optical ground-based measurements at solar wavelength. J. Geophys Res., 93. pp 14223-14231.
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