  Intra-urban origin-destination (OD) network communities evolve throughout the
day, indicating changing groups of closely connected regions. Under this
variation, groups of regions with high consistency of community affiliation
characterize the temporally stable structure of the evolution process, aiding
in comprehending urban dynamics. However, how to quantify this consistency and
identify these groups are open questions. In this study, we introduce the
consensus OD network to quantify the consistency of community affiliation among
regions. Furthermore, the temporally stable community decomposition method is
proposed to identify groups of regions with high internal and low external
consistency (named "stable groups"), where each group consists of temporally
stable cores and attaching peripheries. Wuhan taxi data is used to verify our
methods. On the hourly time scale, eleven stable groups containing 82.9% of
regions are identified. This high percentage suggests that dynamic communities
can be well organized via cores. Moreover, stable groups are spatially closed
and more likely to distribute within a single district and separated by water
bodies. Cores exhibit higher POI entropy and more healthcare and shopping
services than peripheries. Our methods and empirical findings contribute to
some practical issues, such as urban area division, polycentric evaluation and
construction, and infectious disease control.
