Samadi, Mehdi; Boloorani, Ali Darvishi; Alavipanah, Seyed Kazem; Mohamadi, Hossein; Najafi, Mohamad Saeed (2014). Global dust Detection Index (GDDI); a new remotely sensed methodology for dust storms detection. JOURNAL OF ENVIRONMENTAL HEALTH SCIENCE AND ENGINEERING, 12, 20.

Abstract
Dust storm occurs frequently in arid and semi-arid areas of the world. This natural phenomenon, which is the result of stormy winds, raises a lot of dust from desert surfaces and decreases visibility to less than 1 km. In recent years the temporal frequency of occurrences and their spatial extents has been dramatically increased. West of Iran, especially in spring and summer, suffers from significant increases of these events which cause several social and economic problems. Detecting and recognizing the extent of dust storms is very important issue in designing warning systems, management and decreasing the risk of this phenomenon. As the process of monitoring and prediction are related to detection of this phenomenon and it's separation from other atmospheric phenomena such as cloud, so the main aim of this research is establishing an automated process for detection of dust masses. In this study 20 events of dust happened in western part of Iran during 2000-2011 have been recognized and studied. To the aim of detecting dust events we used satellite images of MODIS sensor. Finally a model based on reflectance and thermal infrared bands has been developed. The efficiency of this method has been checked using dust events. Results show that the model has a good performance in all cases. It also has the ability and robustness to be used in any dust storm forecasting and warning system.

DOI:
10.1186/2052-336X-12-20

ISSN:
2052-336X