A novel method for detecting acid rain patterns of SO2 and NO2 using pH in image processing

Acid rain is a major regional scale environmental problem around the globe. To control acid rain pollution and to protect the ecological environment, it is a major need to identify the occurrence of acid rains. This paper presents a methodology for identifying the occurrence of acid rain using pH values calculated from normality by applying k-means clustering and haar wavelet transform on the satellite imagery of water vapor, SO
2
and NO
2
. If the computed pH value lies in the range of 1 ≤ pH ≤ 5, it is identified as acid rain. The resulted outcome indicates that the amount of rainfall with the concentration of SO
2
and NO
2
have a strong influence on the occurrence of acid rains.