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Retrieval of Air Quality using a newly Simulated Algorithm from Aerosol Optical Depth

The optical depth was given by Camagni and Sandroni, (1983), as equation (5). From the equation, we rewrite the optical depth for particle and molecule as equation (6)

where
t = optical depth
s = absorption
s = finite path

Equations (6) are substituted into equation (4). The result was extended to a three-band algorithm as equation (7)

Form the equation; we found that PM10 was linearly related to the reflectance for band 1 and band 2. This algorithm was generated based on the linear relationship between t and reflectance. Retalis et al. also found that the PM10 was linearly related to the t and the correlation coefficient for linear was better that exponential in their study (overall). This means that reflectance was linear with the PM10.

Where
A = particle concentration (PM10)
G = molecule concentration
Ratmi = atmospheric reflectance, i = 1, 2 and 3 are the number of the band
ej = algorithm coefficient, j = 0, 1, 2 and 3 are then empirically determined.

Data Analysis and Results
All the image-processing tasks were carried out using PCI EASI/PACE version 6.2 digital image processing software at the School Of Physics, University of Science Malaysia (USM). The digital images were separated into three bands (red, green and blue) for multispectral algorithm analysis. The average DN for each digital image captured at near and far distance from the reference targets were extracted. Digital images captured near to the reference target were corrected using normalization technique. Presumption made in this study was that the digital imagery captured from near to the reference target was not affected by atmosphere scattering.

A red colour paper was stick on the wall of a building as a reference target. The digital image capture near to the reference target at 9.00 a.m on 5 December 2003 was used as reference image. The difference from the DN value was used to correct for each image captured from near to the target. All the DN values of the digital imageries captured from far to the reference were adjusted according to their correspo0nding difference in the DN values based on the digital images captured from near to the reference target. This normalization technique forced the digital images to have the same illumination condition and the effect due to different solar angle was removed.

All the DN values were then converted into irradiance (equation 1, 2 and 3) using the digital camera coefficients calibrated previously for each bands (Lim, 2003). The irradiances were then converted to reflectance using equation 11 for each band. The solar angles and Earth-Sun distance were calculated corresponding to the acquisition times of the digital images. The mean solar exoatmospheric irradiance values used in this study were 1555 W/m2/mm, 1843 W/m2/mm and 1970 W/m2/mm for the red, green and blue bands respectively.

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