Understanding the relationship between greenhouse gas (GHG) emissions and human activities is essential for effective climate change mitigation. This study applied spatial econometric techniques to analyze CO₂ concentrations using GOSAT L4B data, spatially matched with the Gridded Population of the World Version 4 (GPWv4) in 2020. Spatial matrix and Moran plot were used to detect spatial clustering and anomalies in CO2 distributions across East Asia, which identified regions where the concentrations significantly deviated from expected levels. The results revealed spatial clustering patterns that suggest potential influencing factors such as urban planning and land-use characteristics. These findings emphasized the potential of econometric methods in satellite data analysis and provided insights for regional climate
policies.
