In this paper, we propose spatio-spectral processing techniques for the detection of dust storms and automatically
finding its transport direction in 5-band NOAA-AVHRR imagery. Previous methods that use simple band math
analysis have produced promising results but have drawbacks in producing consistent results when low signal
to noise ratio (SNR) images are used. Moreover, in seeking to automate the dust storm detection, the presence
of clouds in the vicinity of the dust storm creates a challenge in being able to distinguish these two types of
image texture. This paper not only addresses the detection of the dust storm in the imagery, it also attempts
to find the transport direction and the location of the sources of the dust storm. We propose a spatio-spectral
processing approach with two components: visualization and automation. Both approaches are based on digital
image processing techniques including directional analysis and filtering. The visualization technique is intended
to enhance the image in order to locate the dust sources. The automation technique is proposed to detect the
transport direction of the dust storm. These techniques can be used in a system to provide timely warnings of
dust storms or hazard assessments for transportation, aviation, environmental safety, and public health.
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