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


The calibrated digital camera coefficients are


Finally, the data were separated into two group, one consisted of 17 data points for algorithm calibration and the other one consisted of 16 data point for verification analysis. Table 1 shows the algorithm calibration coefficient obtained using the generated algorithm. Figure 2 shown the correlation coefficient and RMS error of the measured and estimated PM10 values for calibration analysis. Figure 3 shows the correlation coefficient and RMS error of the measured and estimated PM10 values for verification analysis.

Table 1: The coefficients for the calibrated algorithm
Algorithm CoefficientsValues
e0-27.1313
e1-8.9957
e2-140.4144
e3873.4354



Figure 2: Correlation coefficient and RMS error of the measured and estimated PM10 values for calibration analysis



Figure 3: Correlation coefficient and RMS error of the measured and estimated PM10 values for verification analysis

Conclusion
We are quite confident with the result produced by this algorithm after verification analysis. This first application of the generated algorithm illustrates the potential use of digital camera imagery for the PM0 estimation. The high correlation was found between the retrieval reflectance and PM10 values gave an indication of the reliability of the generated algorithm. This study gives an economical way for air quality detection. Further work will be carried out to improve the normalization technique and more data are required for verification analysis of the generated algorithm.

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