Name
Abstract | ||
|---|---|---|
Geospatial information systems (GIS) have been applied in modeling environmental and ecological systems. 3D Moving objects
are spatiotemporal objects whose location and/or extent change over time, and they are among those recent evolutions that
emerged to fulfill some of the new requirements for GI community. Many of the earlier works were based on the assumption that
exact trajectory information was available (or could be obtained) at every time instant. Unfortunately, this assumption cannot
be guaranteed in real applications where trajectory information is associated inherently with uncertainty and lack of complete
and precise knowledge. In this paper, we explore how a trajectory is influenced by uncertainty. Then we study the nature of
3D moving object trajectories in the presence of uncertainty and we introduce two data models for uncertain trajectories that
are used to represent moving objects. By using this model in a case study, we obtain the most probable answer where we consider
a 3D moving object path under uncertain conditions and lack of knowledge.
|
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/978-3-540-36998-1_11 | 3D-GIS |
Keywords | Field | DocType |
trajectory uncertainty,sampling error,moving object,temporal gis,uncertainty,data model | Ecological systems theory,Geospatial analysis,Data mining,Data modeling,Instant,Sampling error,Computer science,Artificial intelligence,3D modeling,Machine learning,Trajectory | Conference |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shokri, T | 1 | 0 | 0.34 |
| Mahmoud Reza Delavar | 2 | 106 | 14.99 |
| Mohammad Reza Malek | 3 | 30 | 7.30 |
| Andrew U. Frank | 4 | 835 | 332.71 |
| Gerhard Navratil | 5 | 15 | 4.61 |