Implementation of a very large atmospheric correction lookup table for ASTER using a relational database management system

Alex T. Murray; Bjorn T. Eng; Kurtis J. Thome

doi:10.1117/12.258105

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11 November 1996 Implementation of a very large atmospheric correction lookup table for ASTER using a relational database management system

Alex T. Murray, Bjorn T. Eng, Kurtis J. Thome

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Proceedings Volume 2820, Earth Observing System; (1996) https://doi.org/10.1117/12.258105
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

Abstract

The advanced spaceborne thermal emission and reflection radiometer (ASTER) is designed to provide a high resolution map of the Earth in both visible, near-infrared, and thermal spectral regions of the electromagnetic spectrum. The ASTER science team has developed several standard data product algorithms, but the most complex and computing-intensive of these is the estimation of surface radiance and reflectance values, which is done by modeling and correcting for the effects of the atmosphere. The algorithm for atmospheric correction in the visible bands sensed by ASTER calls fur the use of a very large atmospheric correction look up table (ACLUT). The ACLUT contains coefficients which describe atmospheric effects on ASTER data under various conditions. The parameters used to characterize the atmosphere and its effects on radiation in the ASTER bands include aerosol and molecular optical depth, aerosol size distribution, single scattering albedo, and solar, nadir view, and azimuth angles. The ACLUT coefficients are produced by thousands of runs of a radiative transfer code (RTC) program produced by Phil Slater and Kurt Thome of U. of A. The final version of ACLUT is expected to be in the neighborhood of 10 gigabytes. The RDBMS Sybase is used to manage the process of generating the ACLUT as well as to host the table and service queries on it. Queries on the table are made using ASTER band number and seven floating-point values as keys. The floating-point keys do not necessarily exactly match key values in the database, so the query involves a hierarchical closest-fit search. All aspects of table implementation are described.

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Alex T. Murray, Bjorn T. Eng, and Kurtis J. Thome "Implementation of a very large atmospheric correction lookup table for ASTER using a relational database management system", Proc. SPIE 2820, Earth Observing System, (11 November 1996); https://doi.org/10.1117/12.258105

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