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A technique for improving MODIS standard snow products for snow cover monitoring over Eastern Turkey

Daily snow cover maps at 500 m resolution are available from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on NASA's Terra and Aqua satellites. However, information of the ground can only be obtained during clear sky conditions. In addition, the spectral similarity between c...

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Bibliographic Details
Published in:Arabian journal of geosciences 2012-03, Vol.5 (2), p.353-363
Main Authors: Tekeli, Yaşar, Tekeli, Ahmet Emre
Format: Article
Language:English
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Summary:Daily snow cover maps at 500 m resolution are available from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on NASA's Terra and Aqua satellites. However, information of the ground can only be obtained during clear sky conditions. In addition, the spectral similarity between clouds and snow in the visible part of the spectrum causes some ambiguities in separation of them. The dynamic behavior of clouds with their tendency to move faster often enables discrimination between cloud and snow, since snow remains relatively stationary. In this study, a daily merging methodology to combine Terra and Aqua based snow maps are proposed, and the benefits of this combination are evaluated. The methodology was tested for Eastern Turkey covering the period from December 2002 to March 2003. Merged maps derived from the standard daily snow maps from Terra (MOD10A1) and Aqua (MYD10A1) reduce the cloud cover present in any one image alone, provide better representation of the surface snow cover, and indicate better agreement with ground snow measurements than when either one is used alone. For “on the ground data date” analyses yielded 31% match ratios for MOD10A1 and MYD10A1, whereas combined images enabled 38%. One- to 2-day temporal window shifting enabled further 7% and 5% improvements in match ratios, respectively. The maximum improvement of 25% was achieved in January of 2003. The proposed methodology provides an easy and effective way to improve snow cover maps with little effort and provides fewer cloud-contaminated images for snow monitoring, for hydrology, and water resource management.
ISSN:1866-7511
1866-7538
DOI:10.1007/s12517-010-0274-3