Detection of hydrated dust storms on Modis images in western and southwestern Iran

Dana Rostami (), Hassan Lashkari () and Zainab Mohammadi ()
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Dana Rostami: Shahid Beheshti University (SBU)
Hassan Lashkari: Shahid Beheshti University (SBU)
Zainab Mohammadi: Shahid Beheshti University (SBU)

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 117, issue 2, No 4, 1273-1289

Abstract: Abstract Dust storms have many direct and indirect effects on the environment, climate and air quality. In recent years, dust storms in the western and southwestern of Iran have increased significantly and had destructive effects on the residents of this area. The aim of this study is to develop a multi-spectral algorithm for detecting hydrated dust storms on MODIS images in western and southwestern of Iran. A multi-spectral algorithm was developed using a combination of visible and thermal bands of the MODIS sensor to detect hydrated dust. The studied dust storms events are based on the precipitation at synoptic stations in western and southwestern Iran during synoptic code 06 weather conditions. Based on the spectral and statistical analysis, the brightness temperature difference index of bands 31 and 32 (with a threshold greater than zero) was chosen for the algorithm along with the brightness temperature difference index of the bands 20 and 31 (with a threshold greater than 17) and the logarithm of reflectance bands 1 and 4 (with a threshold greater than − 1.8). A multispectral algorithm was also designed utilizing the above information. The results of the multi-spectral algorithm were validated with MODIS true color images and MODIS optical depth. Validation results revealed that the multi-spectral algorithm is suitable for monitoring hydrated dust in the study area. Results revealed that the multi-spectral algorithm is suitable for monitoring hydrated dust in the study area. Therefore, this method can be used to monitor and predict hydrated dust in this area to reduce potential risks.

Keywords: Hydrated dust; MODIS; Detection algorithm; Remote sensing (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11069-023-05903-4

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