Abstract
The increasing availability of urban trajectory data from the GPS-enabled devices has provided scholars with opportunities to study urban dynamics at a finer spatiotemporal scale. Yet given the multi-dimensionality of urban trajectory dynamics, current research faces challenges of systematically uncovering spatiotemporal and societal implications of human movement patterns. Particularly, a data-driven policy-making process may need to use data from various sources with varying resolutions, analyze data at different levels, and compare the results with different scenarios. As such, a synthesis of varying spatiotemporal and network methods is needed to provide researchers and planning specialists a foundation for studying complex social and spatial processes. In this paper, we propose a framework that combines various spatiotemporal and network analysis units. By customizing the combination of analysis units, the researcher can employ trajectory data to evaluate urban built environment dynamically and comparatively. Two case studies of Chinese cities are carried out to evaluate the usefulness of proposed conceptual framework. Our results suggest that the proposed framework can comprehensively quantify the variation of urban trajectory across various scales and dimensions.
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