Spatial scale is a fundamental issue for geographical phenomena because the size of the spatial unit adopted for analysis can have a significant effect on aggregated spatial data and the corresponding analytical results. There exists much research on the scale issue of spatial distribution data while a few has paid attention to the scale effect on spatial interactions. Big geo-data with micro-level individual movements provide an unprecedented opportunity to explore spatial interactions from the bottom up and to understand the scale effect from the perspective of interaction patterns. In this paper, we introduced an empirical framework to explore spatial interaction data across scales. By incorporating two data sets of taxi trajectories in Beijing and Shanghai, we aggregated the taxi O-D trips under multiple regular grids with different cell sizes and analyzed the properties of spatial interactions in three aspects: the statistical distribution, the distance decay mechanism, and the structure pattern. Our research demonstrated the feasibility of analyzing spatial interactions from a multi-scale view and offered a basic empirical framework for future geographical research that is interested in scale and spatial interactions.
|Original language||English (US)|
|Number of pages||10|
|State||Published - Sep 7 2018|
Bibliographical noteFunding Information:
This work was supported in part by the National Natural Science Foundation of Fujian Province of China under Grant 2018J0106, in part by the Project of Innovation Team of Ningde Normal University under Grant 2017T05, in part by the National Key Research and Development Program of China under Grant 2017YFB05030602, in part by the National Natural Science Foundation of China under Grant 41830645 and Grant 41771425, and in part by the Smart Guangzhou Spatio–temporal Information Cloud Platform Construction under Grant GZIT2016-A5-147.
© 2013 IEEE.
- big geo-data
- regular grids
- spatial interaction
- urban mobility