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Review of dust storm detection algorithms for multispectral satellite sensors
journal contribution
posted on 2023-06-09, 22:18 authored by Jing LI, Man Sing Wong, Kwon Ho Lee, Janet Nichol, P W ChanSatellite remote sensing has been extensively utilized for monitoring dust storms in space and time. Dust storm detection using satellite observations is important to analyze the dust storm trajectories and sources. This paper reviews the algorithms for dust storm detection used in multispectral satellite sensors, spanning visible to thermal wavelengths. Four categories of dust detection algorithms are summarized, namely, dust spectral index algorithms, temporal anomalous detection algorithms, spatial coherence tested algorithms (physical-based algorithms) and machine learning-based algorithms. Following discussions of dust storm detection algorithms, the dust presence validation methods are also reviewed. Future developments for dust storm detection are focused upon three aspects: detection of dust storms at nighttime; development of more efficient machine learning methods for retrieval; and integrating physical and machine learning methods for satellite images.
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Publication status
- Published
Journal
Atmospheric ResearchISSN
0169-8095Publisher
ElsevierExternal DOI
Article number
a105398Department affiliated with
- Geography Publications
Full text available
- No
Peer reviewed?
- Yes
Legacy Posted Date
2020-12-01Usage metrics
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