Name
Abstract | ||
|---|---|---|
Intelligent Transportation Systems are an important enabler for the smart cities paradigm. Currently, such systems generate massive amounts of granular data that can be analyzed to better understand people's dynamics. To address the multivariate nature of spatiotemporal urban mobility data, researchers and practitioners have developed an extensive body of research and interactive visualization tools. Data visualization provides multiple perspectives on data and supports the analytical tasks of domain experts. This article surveys related studies to analyze which topics of urban mobility were addressed and their related phenomena, and to identify the adopted visualization techniques and sensors data types. We highlight research opportunities based on our findings. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3390/s19020332 | SENSORS |
Keywords | Field | DocType |
data visualization,urban mobility,spatiotemporal data,intelligent transportation sytems | Data science,Data visualization,Enabling,Visualization,Electronic engineering,Data type,Interactive visualization,Engineering,Intelligent transportation system,Creative visualization | Journal |
Volume | Issue | ISSN |
19 | 2 | 1424-8220 |
Citations | PageRank | References |
5 | 0.41 | 47 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thiago Sobral | 1 | 5 | 1.42 |
| Teresa GalvãO | 2 | 20 | 5.73 |
| José Borges | 3 | 144 | 12.93 |