Sarikhani, A; Dehghani, M; Karimi-Jashni, A; Saadat, S (2020). A New Approach for Dust Storm Detection Using MODIS Data. IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING.

Dust storms which are considered as a cause of climatic and public health concerns are induced by natural and anthropogenic activities. In this paper, based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images, a new algorithm is developed to automatically detect dust storms over water body and land surfaces. The proposed method applies two different strategies for dust storm detection over water and land surfaces through the combination of various dust indices extracted from reflectance and thermal MODIS channels. It overcomes the disadvantages of previously developed algorithms taking into account the MODIS spectral band 7 (2105-2155 nm) to discriminate between dark and bright land surfaces. Different newly defined dust indices using proper thresholds are then employed for dust storm detection over two land surface classes as well as the water body. The proposed algorithm is applied to six dust-contaminated MODIS images covering southwestern Iran, northeastern Saudi Arabia, and southeastern Iraq. The results show that the proposed dust storm detection method performs well over areas covering features such as bright land surfaces and clouds whose spectral behavior is similar to that of the dust plumes. The results are compared to those obtained from two widely used previously developed dust storm detection algorithms. The comparison of the results with those achieved from visual inspections demonstrates that the proposed method detects the dust storm with the accuracy of similar to 95%, whereas the other two methods result in the dust detection accuracies of similar to 69% and similar to 68%. Furthermore, the proposed approach is found to be promising for dust storm detection over the study area.