Abstract
In recent years, main cities in China have been suffering from hazy weather, which is gaining great attention among the public, government managers and researchers in different areas. Many studies have been conducted on the topic of urban air quality to reveal different aspects of the air quality problem in China. This paper focuses on the visualization problem of the big air quality monitoring data of all main cities on a nationwide scale. To achieve the intuitive visualization of this data set, this study develops two novel visualization tools for multi-granularity time series visualization (timezoom.js) and a dynamic symbol declutter map mashup layer for thematic mapping (symadpative.js). With the two invented tools, we develops an interactive web map visualization application of urban air quality data of all main cities in China. This application shows us significant air pollution findings at the nationwide scale. These results give us clues for further studies on air pollutant characteristics, forecasting and control in China. As the tools are invented for general visualization purposes of geo-referenced time series data, they can be applied to other environmental monitoring data (temperature, precipitation, etc.) through some configurations.
Highlights
Recent years, in China, frequent occurrences of hazy weather in big cities have aroused great attention on urban air quality issues among the public, government managers and academic researchers
The major contributions of this paper are in three aspects: (1) we develop two novel web client tools for interactive visualization of spatio-temporal data; (2) we propose a mashup strategy for web mapping by combining and extending the function of different visualization tools, which can be generalized to visualize other kinds of spatio-temporal data, such as temperature, precipitation, etc.; (3) we implement an on-line interactive urban air quality data visualization application that helps to explore and analyze a big air quality dataset and that puts forward clues for further studies on air pollution
Though this study focuses on air quality monitoring data visualization, the framework and invented visualization tools can be applied to the visualization work of other similar spatio-temporal environmental monitoring data, such as meteorological monitoring data
Summary
In China, frequent occurrences of hazy weather in big cities have aroused great attention on urban air quality issues among the public, government managers and academic researchers. With the increasing availability of urban air quality data and the great environmental challenges we are facing, many studies have been conducted to explore new approaches for understanding this big environmental monitoring dataset. Urban air quality monitoring data consist of many air pollutant concentration values (such as fine particles, carbon monoxide, sulfur dioxide, nitrogen oxides zone, etc.), which are reported hourly from monitoring stations fixed at specific positions in a city. These geo-referenced time series data are an important study subject in the areas of geovisualization and environmental science
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