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dc.contributor.authorAlbugami, S
dc.contributor.authorPalmer, S
dc.contributor.authorMeersmans, J
dc.contributor.authorWaine, T
dc.date.accessioned2019-02-07T16:14:28Z
dc.date.issued2018-12-08
dc.description.abstractSand and dust storm events (SDEs), which result from strong surface winds in arid and semi-arid areas, exhibiting loose dry soil surfaces are detrimental to human health, agricultural land, infrastructure, and transport. The accurate detection of near-surface dust is crucial for quantifying the spatial and temporal occurrence of SDEs globally. The Arabian Peninsula is an important source region for global dust due to the presence of extensive deserts. This paper evaluates the suitability of five different MODIS-based methods for detecting airborne dust over the Arabian Peninsula: (a) Normalized Difference Dust Index (NDDI); (b) Brightness Temperature Difference (BTD) (31-32); (c) BTD (20-31); (d) Middle East Dust Index (MEDI) and (e) Reflective Solar Band (RSB).We derive detection thresholds for each index by comparing observed values for 'dust-present' versus 'dust-free' conditions, taking into account various land cover settings and analyzing associated temporal trends. Our results suggest that the BTD (31-32) method and the RSB index are the most suitable indices for detecting dust storms over different land-cover types across the Arabian Peninsula. The NDDI and BTD (20-31) methods have limitations in identifying dust over multiple land-cover types. Furthermore, the MEDI has been found to be unsuitable for detecting dust in the study area across all land-cover types.en_GB
dc.description.sponsorshipKing Abdulaziz University Scholarshipen_GB
dc.identifier.citationVol. 10: 1993en_GB
dc.identifier.doi10.3390/rs10121993
dc.identifier.urihttp://hdl.handle.net/10871/35822
dc.language.isoenen_GB
dc.publisherMDPIen_GB
dc.rights© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).en_GB
dc.subjectMODISen_GB
dc.subjectremote sensingen_GB
dc.subjectdusten_GB
dc.subjectNDDIen_GB
dc.subjectBTDen_GB
dc.subjectMEDIen_GB
dc.titleEvaluating MODIS dust-detection indices over the Arabian Peninsulaen_GB
dc.typeArticleen_GB
dc.date.available2019-02-07T16:14:28Z
dc.identifier.issn2072-4292
dc.descriptionThis is the final version. Available from the publisher via the DOI in this recorden_GB
dc.identifier.journalRemote Sensingen_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2018-12-03
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2018-12-08
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2019-02-07T16:10:13Z
refterms.versionFCDVoR
refterms.dateFOA2019-02-07T16:14:31Z
refterms.panelCen_GB


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© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's licence is described as © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).