Aerosol Optical Thickness (AOT) Assessment Using GIS & Remote Sensing (International Journal of Innovative Research in Computer Science & Technology, 2018)
Atmospheric aerosol particles are one of the  significant agents of air quality degradation. MODIS,  GIS and Remote Sensing techniques have made the way  of AOT assessment easiest over historic manual  systems. This paper concerns itself with the AOT  assessment using GIS and Remote Sensing over Dhaka,  Bangladesh in 2017. Required observations for AOT  assessment are taken considering seasonal variability.  Considered three seasons for this research are winter  (January, February and December), Pre-monsoon  (March and April) and Post-monsoon (October and  November). Monsoon variations are not considered to  avoid excessive cloud correction. The multispectral  algorithm model is used to detect AOT considering the  surface condition homogenous. Basically, Landsat 8+  OLI images are used for AOT assessment and NASA  Earth Observation (NEO) data are used for data  validation. It is found that the winter season has the  highest concentration of AOT compared to pre and post  monsoon. This is due to the meteorological factors like  cloud, rainfall, humidity, wind pressure and speed,  temperature etc.
Keywords: Aerosol Optical Thickness (AOT); Geographic Information System (GIS); Remote Sensing, Landsat; Image processing