One of the most crucial topics in spatial interaction studies is mining patterns from extensive
origin-destination (OD) flow data to capture interregional associations. However, prevailing …

The prosperity of ride-sharing services has rippled in the communities of GIScience,
transportation, and urban planning. Meanwhile, road network structure has been analyzed …

The detection of colocation pattern is an important and widely used method to analyze the
spatial associations of geographical objects and events. Existing studies primarily focus on …

In the built environment, places such as retail outlets and public sites are embedded in the
spatial context formed by neighboring places. We define the sets of these symbiotic places …

Spatial autocorrelation analysis is essential for understanding the distribution patterns of
spatial flow data. Existing methods focus mainly on the origins and destinations of flow units …

Extracting spatial network structure (SNS) from large-scale origin-destination flow data is an
important approach for understanding interregional association patterns and interaction …

With the rise of geospatial big data, new narratives of cities based on spatial networks and
flows have replaced the traditional focus on locations. While plenty of research that have …

Agent-based models (ABMs) have been widely used to represent and investigate complex
systems and are a contemporary modelling approach used in the study of land-use change …

Exploring how sexual and confidant networks overlap spatially and socially could facilitate a
better understanding of sexually transmitted infection risk, as well as help identify areas for …

The rapid development of the economy promotes the increasing of interactions between
cities and forms complex networks. Many scholars have explored the structural …