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An Assessment of SEVIRI Imagery at Various Temporal Resolutions and the Effect on Accurate Dust Emission Mapping

ARGANS Ltd., 1 Davy Road, Plymouth Science Park, Derriford, Plymouth PL6 8BX, UK
Department of Geography and Environmental Science, University of Reading, Whiteknights, Reading RG6 6AB, UK
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(8), 918;
Received: 25 February 2019 / Revised: 4 April 2019 / Accepted: 9 April 2019 / Published: 16 April 2019
(This article belongs to the Special Issue Remote Sensing in Support of Aeolian Research)
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This paper evaluates the use of the ‘Dust red/green/blue (RGB)’ product derived from Spinning Enhanced Visible and Infrared Imager (SEVIRI) data at 15-min, 30-min, and 60-min temporal resolutions, for monitoring dust emissions in the Middle East. From January 2006 to December 2006, observations of dust emission point sources were recorded at each temporal resolution across the Middle East. Previous work has demonstrated that using SEVIRI data is a major improvement on other remote sensing methods for mapping dust sources in the Sahara, by enabling dust-storm observations through sequential images, back to the point of first emission. However, the highest temporal resolution available (15-min observations) produces 96 images per day, resulting in significantly higher data management requirements than data provided at 30-min and 60-min intervals. To optimize future research workflows, this paper investigates the effect of lowering the temporal resolution on the number and spatial distribution of observed dust emission events in the Middle East. The results show that the number of events observed reduced by 17% for 30-min resolution and 50% for 60-min resolution. These differences change seasonally, with the highest reduction observed in summer (34% and 64% reduction, respectively). View Full-Text
Keywords: atmospheric dust; Meteosat Second Generation; SEVIRI; Middle East atmospheric dust; Meteosat Second Generation; SEVIRI; Middle East

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Hennen, M.; White, K.; Shahgedanova, M. An Assessment of SEVIRI Imagery at Various Temporal Resolutions and the Effect on Accurate Dust Emission Mapping. Remote Sens. 2019, 11, 918.

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