Xudong Yang
ABSTRACT
Some studies have shown that air pollution is one of the important risk factors for human health. In order to find out the transmission mode, space-time patterns, main pollution causes and potential mode of air pollution, we analyzed the multi- granularity and multi-dimensional data, and designed a visual analysis scheme of air pollution data, which integrated time, space and relevant factors, and used many kinds of visual charts, including map, calendar chart, single axis scatter chart and so on. Based on these, a data-driven visual analysis system is designed and implemented, and a variety of visual analysis models are established. The interactive methods such as filtering, scaling and exploration can assist users to carry out the data analysis tasks such as data overview, key data tracking, comparing of correlation, analytic reasoning, hypothesis testing and potential mode discovery, and realize the analysis of key causes, spatiotemporal evolution and transmission mode of air pollution. The system is simple and efficient, which can provide valuable reference for in-depth analysis of air pollution data and evaluation of air pollution control measures.
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