The purpose of this work is to investigate correlation between CO2 concentration and NDVI (Normalized Difference Vegetation Index) in North East Asia. Geographically weighted regression techniques were used to evaluate the spatial relationships between GOSAT (Greenhouse Observing SATellite) CO2 measurement and MODIS (Moderate Resolution Imaging Spectroradiometer) vegetation index. The results reveals that CO2 concentration to be negatively associated with NDVI. The analysis of Global Morans' I

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... ndex and Anselin Local Morasn's I showed spatial autocorrelation between the overall spatial pattern of CO2 and NDVI. Ultimately, there were clustered patterns in both data sets. The results show that carbon dioxide concentration shows non-random distribution patterns in relation to NDVI clusters, which proves that intense development activities such as deforestation are influencing carbon dioxide emission across the area of analysis. However, as the concentration of carbon dioxide varies depending on a variety of factors such as artificial sources, plant respiration, and the absorption and discharge of the ocean, follow-up studies are required to evaluate the correlations among more related variables.