Dust detection and AOT estimation using combined VIR and TIR satellite images in urban areas of Iran


1 Department of Meteorology, Science and Research Branch, Islamic Azad University, Tehran, Iran.

2 Department of Water Engineering, Faculty of Agricultural Sciences, University of Guilan, Guilan, Iran.

3 Institute of Geophysics, University of Tehran, Tehran, P.O. Box 14155-6466, Iran.


This study introduces an empirical equation for estimation of Aerosol Optical Thickness (AOT) and visibility reduction based on three main dust indices of Normalized Di erence Dust Index (NDDI), Brightness Temperature Di erence (BTD), and Thermal infrared Dust Index (TDI). The implementation of NDDI, BTD, and TDI in dust enhancement over bright to dark background was evaluated. The thresholds of BTD over dust and cloud pixels revealed the capability of Moderate Resolution Imaging Spectroradiometer (MODIS) images in separating dust from underlying bright surfaces and clouds. The results indicated that solar reffective bands were insucient to precisely separate dust from clouds, but combination of solar reffective bands and thermal infrared bands synergistically improved the accuracy. The evaluation of results revealed the remarkable correlation of AOT with dust enhancement indices over 11 synoptic stations: BTD (R2 = 0:73), NDDI (R2 = 0:67), and TDI (R2 = 0:71). Hence, AOT and visibility reduction were obtained using multi-regression equation using NDDI and BTD as variables. The accuracy assessment indicated good correlation (R2 = 0:74) between both estimated AOT and the AOT reported by Air Quality Control stations. Moreover, the results con rmed the advantage of proposed AOT as a consistent index for dust enhancement over bright surfaces and dust classi cation as well.