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Visual Analysis of Heterogenous Air Pollution Data

Published: 20 December 2021 Publication History

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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  • (2023)Visual analysis of air pollution spatio-temporal patternsThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-023-02961-439:8(3715-3726)Online publication date: 24-Jun-2023

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cover image ACM Other conferences
CSSE '21: Proceedings of the 4th International Conference on Computer Science and Software Engineering
October 2021
366 pages
ISBN:9781450390675
DOI:10.1145/3494885
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 December 2021

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Author Tags

  1. Air pollution
  2. Spatial and temporal evolution
  3. Visual Analysis

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  • Research-article
  • Research
  • Refereed limited

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  • Sichuan Science and Technology Program

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CSSE 2021

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Overall Acceptance Rate 33 of 74 submissions, 45%

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  • (2023)Visual analysis of air pollution spatio-temporal patternsThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-023-02961-439:8(3715-3726)Online publication date: 24-Jun-2023

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