An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China

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 dataset, 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.

Game-Like 3D Visualisation of Air Quality Data

“…Instead of simply presenting raw data associated to a given geo-location, interfaces can also organise these large amount data for more efficient visualisation. For example, Wey et al [23] proposed a multi-granularity time zooming representation, in which data is presented as a layered set of circles, each layer representing a given time scale. Users move from one layer (e.g., representing months) to another layer (e.g., days) by clicking on a given portion of the former layer.…”

Development of a WebGIS-Based Analysis Tool for Human Health Protection from the Impacts of Prescribed Fire Smoke in Southeastern USA

“…This study aims to directly convey the HiRes2-produced prescribed fire impact forecasts, along with other useful related data, to various users through an online interactive tool for efficient data dissemination, and for a better analysis of air quality and human exposure, as affected by prescribed fires. WebGIS-based online tools have been developed for emissions inventory spatial analysis [9], marine pollution monitoring and forecasting [10], fire danger forecasting [11] and urban air quality monitoring data visualization [12]. Here, we present our efforts in developing a similar interactive online tool for the analysis of monitored and forecasted prescribed fire impacts in southeastern USA.…”

Air Quality Index Prediction using Machine Learning Algorithms

“…Based on this AQI, an area can be categories as good, satisfactory, moderately polluted, poor, very poor, and severe [1]. AQI has been developed and used in many countries to analyze and visualize the air pollutant concentration and take necessary actions to reduce the air pollution [2].…”

“…Mobile monitoring stations are moves to different locations and collect the air quality data for a period of time. Where as fixed will collect the data for a particular location either continuously or periodically [2].…”