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

Naveen Dondapati, K. Suresh Kumar Reddy, Prathyusha Recharla

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    2 Scopus citations

    Abstract

    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, SO2 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 SO2 and NO2 have a strong influence on the occurrence of acid rains.

    Original languageBritish English
    Title of host publicationProceedings of the 2013 International Conference on Green Computing, Communication and Conservation of Energy, ICGCE 2013
    PublisherIEEE Computer Society
    Pages17-22
    Number of pages6
    ISBN (Print)9781467361255
    DOIs
    StatePublished - 2013
    Event2013 International Conference on Green Computing, Communication and Conservation of Energy, ICGCE 2013 - Chennai, Tamil Nadu, India
    Duration: 12 Dec 201314 Dec 2013

    Publication series

    NameProceedings of the 2013 International Conference on Green Computing, Communication and Conservation of Energy, ICGCE 2013

    Conference

    Conference2013 International Conference on Green Computing, Communication and Conservation of Energy, ICGCE 2013
    Country/TerritoryIndia
    CityChennai, Tamil Nadu
    Period12/12/1314/12/13

    Keywords

    • Acid rain
    • Haar wavelet
    • Image processing
    • k-means clustering
    • Normality
    • pH value
    • Precipitation

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