Monitoring and Prediction of Dust and Investigating its Environmental Impacts in the Western Half of Iran and the Eastern Borders of Turkey and Iraq, Using Remote Sensing and GIS

In recent years, the damage caused by dust in different parts has increased dramatically. There are many dusty areas around the world. One of these regions in the southwest of Asia is Iran. The purpose of this study is to model and predict the hazardous dust phenomenon in dusty regions of Iran. For this purpose, dust data from 28 stations of intense dusty areas in Iran were collected at 29-year time intervals. Then, adaptive-network-based fuzzy inference systems (ANFIS) and the core of the radial base function (RBF) models were used for modelling and then the two models were compared to the future exact prediction. Finally, the dust data for all stations are prioritized using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) multivariate decision-making model and output data are mapped by ArcGIS software. According to the results of this study, RMSE of the ANFIS model was 10.5 and the RBF model was 2.18. Therefore, the accuracy of RBF was more than the ANFIS model for prediction of the dust simulated in years, so the RBF model was used to predict. Based on the dust data obtained from the output of the RBF model in both the mean and maximum of dust abundance, the western and southwestern stations of the study areas were more exposed to dust in the future. Also, according to TOPSIS model, in the prioritization of stations involved with dust for simulated years, Abadan, Masjed Soleyman and Ahwaz were ranked by the amount of 100, 95% and 81%, respectively. Dust is one of the atmospheric phenomena that have adverse environmental effects and consequences. Dust storms have detrimental effects on the health and economy of society and climate change. Understanding the nature, origin and effects of dust storms plays an important role in determining its control methods.