Visual analytics for characterizing mobility aspects of urban context

Autor: Mirco Nanni, Ansar Yasar, Robert Weibel, Harris V. Georgiou, Nikos Pelekis, Christos Doulkeridis, Ibad Kureshi, Haosheng Huang, Natalia Andrienko, Siming Chen, Leonardo Longhi, Fabian Patterson, Athanasios Koumparos, Gennady Andrienko, Yannis Theodoridis
Přispěvatelé: Shi, Wenzhong, Goodchild, Michael F., Batty, Michael, Kwan, Mei-Po, Zhang, Anshu
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Urban informatics
Urban Informatics ISBN: 9789811589829
ISSN: 2365-757X
2365-7588
Popis: Visual analytics science develops principles and methods for efficient human–computer collaboration in solving complex problems. Visual and interactive techniques are used to create conditions in which human analysts can effectively utilize their unique capabilities: the power of seeing, interpreting, linking, and reasoning. Visual analytics research deals with various types of data and analysis tasks from numerous application domains. A prominent research topic is analysis of spatiotemporal data, which may describe events occurring at different spatial locations, changes of attribute values associated with places or spatial objects, or movements of people, vehicles, or other objects. Such kinds of data are abundant in urban applications. Movement data are a quintessential type of spatiotemporal data because they can be considered from multiple perspectives as trajectories, as spatial events, and as changes of space-related attribute values. By example of movement data, we demonstrate the utilization of visual analytics techniques and approaches in data exploration and analysis.
Databáze: OpenAIRE