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

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 pr...

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Main Authors: Wei Lu, Tinghua Ai, Xiang Zhang, Yakun He
Format: Article
Language:English
Published: MDPI AG 2017-08-01
Series:Atmosphere
Subjects:
Online Access:https://www.mdpi.com/2073-4433/8/8/148
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spelling doaj-edcfca56d675458a8b79a2f395a7c4f62020-11-24T22:52:54ZengMDPI AGAtmosphere2073-44332017-08-018814810.3390/atmos8080148atmos8080148An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of ChinaWei Lu0Tinghua Ai1Xiang Zhang2Yakun He3School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, ChinaSchool of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, ChinaSchool of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, ChinaSchool of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, ChinaIn 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.https://www.mdpi.com/2073-4433/8/8/148air qualityenvironmental data visualizationspatial-temporal visualizationvisual analytics
collection DOAJ
language English
format Article
sources DOAJ
author Wei Lu
Tinghua Ai
Xiang Zhang
Yakun He
spellingShingle Wei Lu
Tinghua Ai
Xiang Zhang
Yakun He
An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China
Atmosphere
air quality
environmental data visualization
spatial-temporal visualization
visual analytics
author_facet Wei Lu
Tinghua Ai
Xiang Zhang
Yakun He
author_sort Wei Lu
title An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China
title_short An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China
title_full An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China
title_fullStr An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China
title_full_unstemmed An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China
title_sort interactive web mapping visualization of urban air quality monitoring data of china
publisher MDPI AG
series Atmosphere
issn 2073-4433
publishDate 2017-08-01
description 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.
topic air quality
environmental data visualization
spatial-temporal visualization
visual analytics
url https://www.mdpi.com/2073-4433/8/8/148
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