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Ozone is one of the most effective pollutants in lower atmosphere. Concentration of ozone in atmosphere reveals its impact on plants, human and on other organic materials. Many techniques had been used in past to calculate the concentration of ozone with the help of other environmental factors like wind, humidity, rainfall, temperature and etc. Prediction models like artificial neural network have gained much reputation in calculating accurate results with learning data. This paper shows a study of integration of predicted ozone concentration from neural network and GIS. The study initiated with data collection from the study area. The collected data is then fed to neural network as training data to get the concentrations of ozone with input variables temperature, humidity and rainfall.
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