Trajectory similarity measurement model considering geographic semantics

doi:10.13474/j.cnki.11-2246.2023.0074

Abstract

Abstract: The motion behaviour of moving objects is often influenced by the geographical environment in which they are located. In response to the current situation that existing trajectory similarity analysis often fails to take into account the geographical environment, a multiple motion feature trajectory similarity measure that takes into account geographical semantics is proposed. The method is based on a data cube that extends to the temporal level, and symbolises the geographic semantics and motion features of the trajectory sequence. Finally, this similarity measure is combined with spectral clustering to explore the motion behaviour and patterns of moving objects, and the validity and advantages of the model are verified using real data.

Key words: geographical environment, geosemantics, movement trajectories, movement characteristics, spatio-temporal cubes

CLC Number:

P208

ZHOU Huijun, LUO Shijia, JIANG Heping, ZHANG Jing. Trajectory similarity measurement model considering geographic semantics[J]. Bulletin of Surveying and Mapping, 2023, 0(3): 67-73,149.

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