Dimension Expansion-based Spatiotemporal Land Cover Change Detection: A Study Case Using Sentinel-2 Satellite Time Series

Air pollution harms health and society. Understanding and predicting it is crucial. Various models have been developed to model air pollution. However, the consistency exhibited by a model in different areas is commonly neglected. Our study accounts for this and shows lower accuracy near busy roads but higher accuracy in less populated areas. Considering location characteristics in air pollution predictions is important in comparing statistical models and understanding the health–society–space relationship.