Publication Type:

Conference Paper


2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI) (2017)


aerosol, aerosols, Air pollution, asbestos, asbestos sheets, building roofs, Cirrus and TIR, coal combustion, Earth, environmental science computing, Feature extraction, geophysical image processing, image classification, Image processing, Land surface, Land surface temperature, land surface temperature map, landsat 8 data, Multispectral, multispectral imaging, pollution content, pollution control, SWIR, Temperature distribution, Thermal Infrared, urban area, Urban areas, urban environment, urban object classification, Vegetation mapping


Pollution control is a challenging task in current scenario. The very first step to control pollution is to detect the sources of pollution. The urban areas are more polluted than rural due to the high population density. The pollutants considered in this paper are aerosol and asbestos sheets. The source of asbestos are building roofs which are mainly in urban area and that of aerosol is combustion of coal. The conventional image processing techniques failed to detect the pollutant in urban environment which can be performed well using multispectral imaging. Since each object has different temperatures using the TIR (Thermal Infrared) bands of Landsat 8 data, the urban objects are classified using the land surface temperature map. The presence of asbestos sheets is detected by change in intensity of images with respect to Band 7 (Short Wave Infrared) and Band 9 (Cirrus). Aerosol is comprised of components that cause air pollution. In this work, the PM10 value is considered as one of the measures to identify the concentration of particulate matters in specific area.

Cite this Research Publication

J. E. George, Aravinth J., and S. Veni, “Detection of Pollution Content in an Urban Area Using Landsat 8 Data”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2017.