Visual Analytics of Air Pollution Transmission Among Urban Agglomerations

In field of air quality research, it is essential to scientifically reflect the internal structure of air quality distribution and reveal the dynamic evolution of air pollution. In this study, a novel visual analytics method is proposed to address these challenges. Initially, the spatio-temporal features of air quality data are mined to complete urban agglomeration division based on dimensionality reduction and clustering. Subsequently, the air pollution transmission network (APTN) is constructed through particle transport and correlation analysis. A progressive exploration analysis method based on multidimensional space transformation is then employed to explore the process of air pollution transmission. Furthermore, a visual analytics system is developed to facilitate the interpretation of the results. Finally, we demonstrate the effectiveness of our proposed methodology using real data sets and case studies, and receive positive feedback from domain experts.