Aerosol Optical Thickness (AOT) Assessment Using GIS & Remote Sensing
Keywords:
Aerosol Optical Thickness (AOT), Geographic Information System (GIS), Remote Sensing, , Landsat, Image processingAbstract
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.
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