Yes / Dust storms are one of the natural phenomena, which
have increased in frequency in recent years in North Africa, Australia
and northern China. Satellite remote sensing is the common
method for monitoring dust storms but its use for identifying dust
storms over sandy ground is still limited as the two share similar
characteristics. In this study, an artificial neural network (ANN)
is used to detect dust storm using 46 sets of data acquired between
2001 and 2010 over North Africa by the Moderate Resolution
Imaging Spectroradiometer (MODIS) instruments aboard the
Terra and Aqua satellites. The ANN uses image data generated
from Brightness Temperature Difference (BTD) between bands
23 and 31 and BTD between bands 31 and 32 with three bands
1, 3, and 4, to classify individual pixels on the basis of their
multiple-band values. In comparison with the manually detection
of dust storms, the ANN approach gave better result than the
Thermal Infrared Integrated Dust Index approach for dust storms
detection over the Sahara. The trained ANN using data from the
Sahara desert gave an accuracy of 0.88 when tested on data from
the Gobi desert and managed to detect 90 out of the 96 dust storm
events captured worldwide by Terra and Aqua satellites in 2011
that were classified as dusty images on NASA Earth Observatory. / IEEE Geoscience and Remote Sensing Society
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/7676 |
| Date | 07 February 2013 |
| Creators | El-Ossta, Esam E.A., Qahwaji, Rami S.R., Ipson, Stanley S. |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Article, Accepted Manuscript |
| Rights | © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
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