The relationship between the built environment and nonwork travels reveals potential supply-
demand status between urban functional facilities and diverse living travels, which provide …

Spatial flow co-location patterns (FCLPs) are important for understanding the spatial
dynamics and associations of movements. However, conventional point-based co-location …

Detecting regional co-location patterns on urban road networks is challenging because it is
computationally prohibitive to search all potential co-location patterns and their localities …

多模态地理大数据时空分析旨在融合地理大数据的多模态信息发现有价值的时空分布规律,
异常表现, 关联模式与变化趋势, 是全空间信息系统的核心研究内容, 并有望成为推进地理学人地 …

Multilevel co-location patterns embedded in spatial datasets are difficult to discern due to the
complexity of neighboring relationships among spatial features. The neighboring …

In many central districts in cities across the world, different types of stores form clusters
resulting from the benefits of spatial agglomeration. To precisely analyze co-location …

Regions of anomalous spatial co-locations (ROASCs) are regions where co-locations
between two different features are significantly stronger or weaker than expected. ROASC …

Network K-function has been the de facto operation for analyzing point patterns in spatial
networks, which is widely used in many communities, including geography, ecology …

Infectious disease diffusion is inherently a complex spatiotemporal phenomenon.
Simplifying this complexity to discover the associated structure of the city is of great …

Given instances (spatial points) of different spatial features (categories), significant spatial co-
distribution pattern discovery aims to find subsets of spatial features whose spatial …