:: Volume 6, Issue 1 (6-2018) ::
jgit 2018, 6(1): 171-184 Back to browse issues page
Distribution of atmospheric NO2 in the industrial cities using OMI and MODIS images (Case study: Tehran metropolis)
Abolfazl Ahmadian *, Mohammad Reza Mobasheri, Ali Akbar Matkan
K. N. Toosi University of Technology
Abstract:   (2282 Views)
The atmosphere is a complicated and dynamic system containing natural gases as well as some extra gases produced through different sources. Concentration of suspended particles in the atmosphere is one of the most important indicators of air pollution. Tehran is among the most polluted cities in the world. Being able to determine the amount of pollution in the city’s air, may lead to strategies being adopted for reduction of its negative effects. Commonly, measurement of the air pollution is carried out by gauges installed in stations all around the city. These limited number of gauges can precisely measure pollution within the station zone. However, the measured data is not valid for the regions far from stations. NO2 is one of the most important factors in the air pollution; hence this study attempts to determine it in urban areas using remote sensing. OMI images are routinely providing air pollution data on a daily basis. These images give the amounts of pollution in large pixels which are not appropriate for urban areas. In this study, the concurrent images of MODIS and OMI were used in order to find a relation between pollution and reflectance in different bands. At first, the relationship between pollution and reflectance in industrial areas and large cities were determined. Then different combinations of equations were considered for MODIS bands and the best combination was chosen. At the end, distribution image of pollution was obtained in the city. Evaluation of this equation shows acceptable accuracy in prediction of NO2 by MODIS images. In addition, critical and highly polluted areas were determined by accumulation of air pollution images on different days. At the end, data of ground stations were utilized in order to evaluate acquired results (RMSE=0.29 and RRMSE=44.3%). The model showed small relative errors (15%) for large amounts of NO2 and huge errors (100%) for low amounts of pollution.
Keywords: Remote Sensing, Air Pollution, Nitrogen dioxide, MODIS, OMI
Full-Text [PDF 2346 kb]   (915 Downloads)    
Type of Study: Research | Subject: RS
Received: 2016/04/18 | Accepted: 2016/08/29 | Published: 2018/06/21

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Volume 6, Issue 1 (6-2018) Back to browse issues page