Time series is a time-oriented or chronological sequence of observations on a variable of interest. AutoRegressive Integrated Moving Average (ARIMA) model approach was used in this study for time series analysis of NO2 concentration in Punjab region, India. Kriging Spatial Interpolation method was also used. This study integrated the satellite observed data with statistical methods. The predicted NO2 concentration was used for spatial distribution and estimation of NO2. OMI satellite data for tropospheric NO2 from the year 2012 to 2019 were used to make a forecast of NO2 concentrations for the year 2020. The R2 value showed good agreement between the observed and predicted concentrations of NO2 in both the approaches.
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GIS and Time Series Modelling Approach to Predict Tropospheric Nitrogen Dioxide
- CHADETRIK ROUT 1,
- GAURAV SHUKLA 1,
- VIKAS BENIWAL 2,
- SURENDRA PAL SINGH 3,
- RAHUL RAHUL 1,*
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Received: 04 Jan 2022 | Accepted: 10 Mar 2022
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Volume 27, Issue 1How to Cite
ROUT, C.; SHUKLA, G.; BENIWAL, V.; SINGH, S. P.; RAHUL, R. GIS and Time Series Modelling Approach to Predict Tropospheric Nitrogen Dioxide. Annals of Agri-bio Research 2022, 27 (1), 35–41.
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