A Spatiotemporal Trajectory Data Index Based on the Hilbert Curve Code

Abstract

Massive trajectory data have been accumulated with the rapid development of global positioning technology and the popularisation of intelligent mobile terminal. However, the generation of massive data does not necessarily lead to the increase in effective data. An index method meeting the efficient management requirements of spatiotemporal trajectory data needs to be designed for the efficient spatiotemporal analysis and calculation of data. This paper proposes a spatiotemporal index method based on the Hilbert curve code to solve this problem. Firstly, the method constructs a multi-scale spatiotemporal grid model covering the whole world by dividing the three-dimensional space composed of time, latitude and longitude. Secondly, the grid cell codes are designed based on the Hilbert curve for hierarchical organisation of the trajectory data. Finally, the corresponding query process based on the code index is proposed in accordance with the different spatiotemporal query requirements of trajectory data. The comparison experiments show that the proposed method is more efficient than the existing spatiotemporal index method and can effectively support the management of massive multi-scale trajectory data.