A survey of urban visual analytics: Advances and future directions

Developing effective visual analytics systems demands care in characterization of domain problems and integration of visualization techniques and computational models. Urban visual analytics has already achieved remarkable success in tackling urban problems and providing fundamental services for sma...

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Detalles Bibliográficos
Autores principales: Deng, Zikun, Weng, Di, Liu, Shuhan, Tian, Yuan, Xu, Mingliang, Wu, Yingcai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Tsinghua University Press 2022
Materias:
Review Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9579670/
https://www.ncbi.nlm.nih.gov/pubmed/36277276
http://dx.doi.org/10.1007/s41095-022-0275-7
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author Deng, Zikun
Weng, Di
Liu, Shuhan
Tian, Yuan
Xu, Mingliang
Wu, Yingcai
author_facet Deng, Zikun
Weng, Di
Liu, Shuhan
Tian, Yuan
Xu, Mingliang
Wu, Yingcai
author_sort Deng, Zikun
collection PubMed
description Developing effective visual analytics systems demands care in characterization of domain problems and integration of visualization techniques and computational models. Urban visual analytics has already achieved remarkable success in tackling urban problems and providing fundamental services for smart cities. To promote further academic research and assist the development of industrial urban analytics systems, we comprehensively review urban visual analytics studies from four perspectives. In particular, we identify 8 urban domains and 22 types of popular visualization, analyze 7 types of computational method, and categorize existing systems into 4 types based on their integration of visualization techniques and computational models. We conclude with potential research directions and opportunities. [Image: see text]
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spelling pubmed-95796702022-10-19 A survey of urban visual analytics: Advances and future directions Deng, Zikun Weng, Di Liu, Shuhan Tian, Yuan Xu, Mingliang Wu, Yingcai Comput Vis Media (Beijing) Review Article Developing effective visual analytics systems demands care in characterization of domain problems and integration of visualization techniques and computational models. Urban visual analytics has already achieved remarkable success in tackling urban problems and providing fundamental services for smart cities. To promote further academic research and assist the development of industrial urban analytics systems, we comprehensively review urban visual analytics studies from four perspectives. In particular, we identify 8 urban domains and 22 types of popular visualization, analyze 7 types of computational method, and categorize existing systems into 4 types based on their integration of visualization techniques and computational models. We conclude with potential research directions and opportunities. [Image: see text] Tsinghua University Press 2022-10-18 2023 /pmc/articles/PMC9579670/ /pubmed/36277276 http://dx.doi.org/10.1007/s41095-022-0275-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . Other papers from this open access journal are available free of charge from http://www.springer.com/journal/41095. To submit a manuscript, please go to https://www.editorialmanager.com/cvmj.
spellingShingle Review Article
Deng, Zikun
Weng, Di
Liu, Shuhan
Tian, Yuan
Xu, Mingliang
Wu, Yingcai
A survey of urban visual analytics: Advances and future directions
title A survey of urban visual analytics: Advances and future directions
title_full A survey of urban visual analytics: Advances and future directions
title_fullStr A survey of urban visual analytics: Advances and future directions
title_full_unstemmed A survey of urban visual analytics: Advances and future directions
title_short A survey of urban visual analytics: Advances and future directions
title_sort survey of urban visual analytics: advances and future directions
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9579670/
https://www.ncbi.nlm.nih.gov/pubmed/36277276
http://dx.doi.org/10.1007/s41095-022-0275-7
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