TY - JOUR
T1 - SparseTrajAnalytics
T2 - an Interactive Visual Analytics System for Sparse Trajectory Data
AU - Ye, Xinyue
AU - Du, Jiaxin
AU - Gong, Xi
AU - Zhao, Ye
AU - AL-Dohuki, Shamal
AU - Kamw, Farah
N1 - Funding Information:
We greatly appreciate the valuable comments and suggestions from the editors and anonymous reviewers. This material is partially based upon work supported by the National Science Foundation under Grant Nos. 1739491 and 1937908. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.
Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2021/6
Y1 - 2021/6
N2 - Sparse trajectory data are trajectories that cover a relatively large geographic area with infrequent samplings of movements, such as human migration and hurricane trajectories. Compared with dense trajectory data (e.g., massive vehicle movements in a metropolitan area), sparse trajectories represent a more general form of movement data due to the data availability and less sensitivity. However, there is a lack of open source software for sparse trajectory data analytics. We designed an online system with a self-adaptive heatmap and multi-spatial-temporal-view charts to analyze sparse trajectories both visually and interactively. With our system, users can (1) store and manage sparse trajectory data on a cloud service; (2) analyze sparse movement behaviors by querying consolidated and live data sets using keywords, spatial location, and time constraints; and (3) explore query results and associated data through web-based thematic maps, tables, and charts. Results of the survey among domain experts show that the open source system is intuitive and user-friendly.
AB - Sparse trajectory data are trajectories that cover a relatively large geographic area with infrequent samplings of movements, such as human migration and hurricane trajectories. Compared with dense trajectory data (e.g., massive vehicle movements in a metropolitan area), sparse trajectories represent a more general form of movement data due to the data availability and less sensitivity. However, there is a lack of open source software for sparse trajectory data analytics. We designed an online system with a self-adaptive heatmap and multi-spatial-temporal-view charts to analyze sparse trajectories both visually and interactively. With our system, users can (1) store and manage sparse trajectory data on a cloud service; (2) analyze sparse movement behaviors by querying consolidated and live data sets using keywords, spatial location, and time constraints; and (3) explore query results and associated data through web-based thematic maps, tables, and charts. Results of the survey among domain experts show that the open source system is intuitive and user-friendly.
KW - Human migration
KW - Hurricane trajectories
KW - Sparse trajectories
KW - Visual analytics
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U2 - 10.1007/s41651-020-00068-1
DO - 10.1007/s41651-020-00068-1
M3 - Article
AN - SCOPUS:85104422480
SN - 2509-8829
VL - 5
JO - Journal of Geovisualization and Spatial Analysis
JF - Journal of Geovisualization and Spatial Analysis
IS - 1
M1 - 3
ER -