Evaluating MODIS dust-detection indices over the Arabian Peninsula

Date

2018-12-08

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

MDPI

Department

Type

Article

ISSN

2072-4292

Format

Free to read from

Citation

Sarah Albugami, Steven Palmer, Jeroen Meersmans and Toby Waine. Evaluating MODIS dust-detection indices over the Arabian Peninsula. Remote Sensing, 2018, Volume 10, Issue 12, Article number 1993

Abstract

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.

Description

Software Description

Software Language

Github

Keywords

MODIS, remote sensing, dust, NDDI, BTD, MEDI

DOI

Rights

Attribution 4.0 International

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