A survey of visual analytics in urban area

Feng, Zezheng1,2,3; Qu, Huamin1; Yang, Shuang-Hua2,4; Ding, Yulong2,3,4; Song, Jie5

2022-07-01

10.1111/exsy.13065

EXPERT SYSTEMS   Impact Factor & Quartile

0266-4720

1468-0394

Nowadays, the population has been overgrowing due to urbanization, yielding many severe problems in the urban area, including traffic congestion, unbalanced distribution of urban hotspots, air pollution and so on. Due to the uncertainty of the urban environment, it always needs to integrate experts' domain knowledge into solving these issues. In recent years, the visual analytics method has been widely used to assist domain experts in solving urban problems with its intuitiveness, interactivity and interpretability. In this survey, we first introduce the background of urban computing, present the motivation of visual analytics in the urban area and point out the characteristics of visual analytics methods. Second, we introduce the most frequently used urban data, analyse the main properties and provide an overview on how to use these data. Thereafter, we propose our taxonomy for visual analytics in the urban area and illustrate the taxonomy. The taxonomy provides four levels for visual analytics on urban data from a new perspective based on the four stages in data mining. Four levels from our taxonomy include: descriptive analytics, diagnostic analytics, predictive analytics and prescriptive analytics. Finally, we conclude this survey by discussing the limitations of the existing related works and the challenges to visual analytics in the urban area.

data mining urban data visual analytics visualization

SCI ; EI

English

Corresponding

National Key Research and Development Plans of P. R. China[2019YFC0810705] ; National Natural Science Foundation of China["92067109","61873119"] ; Shenzhen Fundamental Research Program[JCYJ20200109141218676] ; Shenzhen Key Laboratory Establishment Program[ZDSYS20210623092007023] ; Science and Technology Planning Project of Guangdong Province[2021A0505030001] ; Educational Commission of Guangdong Province[2019KZDZX1018]

Computer Science

Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods

WOS:000826516300001

WILEY

20223112455314

Data mining ; Data visualization ; Domain Knowledge ; Predictive analytics ; Surveys ; Taxonomies ; Traffic congestion

Data Processing and Image Processing:723.2 ; Artificial Intelligence:723.4 ; Computer Applications:723.5 ; Information Science:903

COMPUTER SCIENCE

Web of Science

1.Hong Kong Univ Sci & Technol, Dept Comp Sci & Engn, Kowloon, Hong Kong, Peoples R China
2.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Shenzhen, Guangdong, Peoples R China
3.Northeastern Univ, Dept Software Coll, Shenyang, Liaoning, Peoples R China
4.Southern Univ Sci & Technol, Shenzhen Key Lab Safety & Secur Next Generat Ind, Shenzhen, Guangdong, Peoples R China
5.Southern Univ Sci & Technol, Acad Adv Interdisciplinary Studies, Shenzhen, Guangdong, Peoples R China

Feng, Zezheng,Qu, Huamin,Yang, Shuang-Hua,et al. A survey of visual analytics in urban area[J]. EXPERT SYSTEMS,2022.

Feng, Zezheng,Qu, Huamin,Yang, Shuang-Hua,Ding, Yulong,&Song, Jie.(2022).A survey of visual analytics in urban area.EXPERT SYSTEMS.

Feng, Zezheng,et al."A survey of visual analytics in urban area".EXPERT SYSTEMS (2022).