Name
Abstract | ||
|---|---|---|
Spatiotemporal proximity analysis to determine spatiotemporal proximal paths is a critical step for many movement analysis methods. However, few effective methods have been developed in the literature for spatiotemporal proximity analysis of movement data. Therefore, this study proposes a space-time-integrated approach for spatiotemporal proximal analysis considering space and time dimensions simultaneously. The proposed approach is based on space-time buffering, which is a natural extension of conventional spatial buffering operation to space and time dimensions. Given a space-time path and spatial tolerance, space-time buffering constructs a space-time region by continuously generating spatial buffers for any location along the space-time path. The constructed space-time region can delimit all space-time locations whose spatial distances to the target trajectory are less than a given tolerance. Five space-time overlapping operations based on this space-time buffering are proposed to retrieve all spatiotemporal proximal trajectories to the target space-time path, in terms of different spatiotemporal proximity metrics of space-time paths, such as Frechet distance and longest common subsequence. The proposed approach is extended to analyze space-time paths constrained in road networks. The compressed linear reference technique is adopted to implement the proposed approach for spatiotemporal proximity analysis in large movement datasets. A case study using real-world movement data verifies that the proposed approach can efficiently retrieve spatiotemporal proximal paths constrained in road networks from a large movement database, and has significant computational advantage over conventional space-time separated approaches. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1080/13658816.2018.1432862 | INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE |
Keywords | Field | DocType |
Space-time buffering, space-time overlapping, spatiotemporal proximity, movement data, time geography | Movement analysis,Space time,Computer vision,Data mining,Computer science,Spacetime,Time geography,Artificial intelligence,Trajectory | Journal |
Volume | Issue | ISSN |
32 | 6 | 1365-8816 |
Citations | PageRank | References |
0 | 0.34 | 28 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hui Yuan | 1 | 52 | 2.82 |
| Bi Yu Chen | 2 | 107 | 6.79 |
| Qingquan Li | 3 | 1181 | 135.06 |
| Shih-Lung Shaw | 4 | 341 | 23.87 |
| William H. K. Lam | 5 | 174 | 20.40 |