Remote Sensing of Aerosols over Penang Island from Satellite Measurements

Remotely sensed can be the only data source in rural and remote areas where no ground-based measurements are taken. This image is used to detect air pollution at regional level, in coarser resolution. Remotely sensed data can be used qualitatively to provide a regional view of pollutants and to help assess the impact of events such as biomass burning or dust transport from remote sources. In this study, we explored the relationship between particulate matters of size less than 10 micron (PM10) derived from the Landsat TM using regression technique. We was developed a new algorithm that can effectively estimate the spatial distribution of atmospheric aerosols and retrieve surface reflectance from remotely sensed imagery. The algorithm was developed base on the aerosol characteristics in the atmosphere and the algorithm is modified to accommodate the visible and thermal bands of Landsat TM5 image. We were obtained the atmospheric reflectance values by subtracting surface reflectance from the amount of reflectance measured from the satellite. The satellite recorded reflectance is the sum of the surface reflectance and atmospheric reflectance. The efficiency of the developed algorithm, in comparison to other forms of algorithm, will be investigated in this study. Based on the values of the correlation coefficient and root-mean-square deviation, the proposed algorithm is considered superior. The calibrated algorithm will be used to generate the air quality maps over Penang Island, Malaysia. The finding obtained by this study indicates that the Landsat TM data can be used to retrieved air quality information for remotely sensed data.