Iranian Journal of Remote Sensing and GIS

Iranian Journal of Remote Sensing and GIS

Presentation And Evaluation of A New Spatiotemporal Model For Dust Emission In Regional Scale(DustEM)

Document Type : علمی - پژوهشی

Authors
E Khodabandehloo 1
A Alimohamdadi 2
A Sadeghi-Niaraki 3
A Darvishi Boloorani 4
A.A Alesheikh 2
1 GIS student Department of GIS Engineering, Geomatics Engineering Faculty, K.N. Toosi University of Technology
2 Associate Prof., Department of GIS Engineering, Geomatics Engineering Faculty, K.N. Toosi University of Technology
3 Assistant Prof., Department of GIS Engineering, Geomatics Engineering Faculty, K.N. Toosi University of Technology
4 Assistant Prof.,University of Tehran Faculty of Geography, Dep. Of Remote Sensing & GIS, Geoinformatics Research Institute (UT-RGI) and University of Tehran
Abstract
Dust storm has been one of the most important challenges of western Asia. This phenomenon has been intensified due to the drought and has many negative effects on people's lives.  Since this region located in a dust belt in the world, it is necessary to explore different aspects of this phenomenon is well. Predictive and modeling of this phenomenon can be prevented of jeopardizing the lives of millions of people. So present a Regional Model to assess different aspects of this phenomenon is necessary.  Since climate and weather elements are constantly changing, the spatiotemporal model should be used for modeling and visualization. Hence, a model for estimating dust emission has been designed and developed and Geographic Information System (GIS) spatial modeling capabilities and remote sensing (RS) data (wind speed, soil moisture, soil texture and digital elevation model) are used. The model which is called DustEM calculates horizontal dust emission. In this study, modeling is done for 2001 to 2007 and model’s output is evaluated by MODIS AOD and for dictating hot spot area output is clustered in 3 categories contain high, medium and low with threshold 0.3 and 0.6 for AOD. Accuracy index mean for the study period was 73.6% and show high precision of model in detecting hot spot area.
Keywords
Spatiotemporal Modeling
Dust Sources
GIS
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