Evaluating MODIS dust-detection indices over the Arabian Peninsula

BTD; Dust; MEDI; MODIS; NDDI; Remote sensing; Arid regions; Radiometers; Storms; Arid and semi-arid areas; Brightness temperature difference; Normalized differences; Reflective solar bands; Sand and dust storms

Abstract :

[en] Sand 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. © 2018 by the authors.

Disciplines :

Environmental sciences & ecology

Author, co-author :

Albugami, S.; College of Life and Environmental Sciences, University of Exeter, Exeter, EX4 4RJ, United Kingdom

Palmer, S.; College of Life and Environmental Sciences, University of Exeter, Exeter, EX4 4RJ, United Kingdom

Meersmans, Jeroen ; Université de Liège - ULiège > Département GxABT > Analyse des risques environnementaux

Waine, T.; Soil and Agrifood Institute, Cranfield University, Cranfield, MK43 0AL, United Kingdom

Language :

English

Title :

Evaluating MODIS dust-detection indices over the Arabian Peninsula

Publication date :

2018

Journal title :

Remote Sensing

eISSN :

2072-4292

Publisher :

MDPI AG

Volume :

Issue :

Peer reviewed :

Peer Reviewed verified by ORBi

Funders :

University of Exeter
KAUST - King Abdullah University of Science and Technology

Available on ORBi :

since 08 November 2021

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