Detection And Validation Of Dust Storm From Npp Viirs

2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)(2017)

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Abstract
A dust storm detection algorithm for NPP VIIRS data is proposed in this paper. The pixel dataset includes a variety of typical feature types, such as dust over different surface type, thick and thin clouds, vegetation, Gobi, ice/snow, etc. were collected and the distribution of the reflectance and brightness temperature were analyzed, based on which, a dust detection algorithm was generated. Multi-temporal NPP VIIRS images with dust storm happened were collected and applied to the experiments of dust storm detection with the proposed method. OMI AI products which can well describe the distribution of dust storm were selected for validation, and the results shows that this algorithm can detect the dust storm from NPP VIIRS over different land types in high precision.
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Key words
dust detection, pixel dataset, NPP VIIRS, Brightness Temperature, OMI AI
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