There is a growing body of literature investigating whether social media posts can improve
understanding spatial density in relation to urban park use and how park facilities play a role …

空间交互是理解地表人文过程的重要基础, 与空间依赖一起共同体现了地理空间的独特性,
关联性以及对嵌入该空间的地理分布格局的影响, 具有鲜明的时空属性, 因此对于地理学研究 …

Spatial flow data represent meaningful spatial interaction (SI) phenomena between
geographic regions that are often highly dynamic. However, most existing flow analytical …

Extracting flow clusters consisting of many similar origin–destination (OD) trips is essential to
uncover the spatio-temporal interactions and mobility patterns in the free-floating bike …

Geographical flow (hereafter flow) can be modeled as an orderly connected point pair
composed of an origin (O) and a destination (D). Aggregation is the most common form of …

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 …

Spatial flow outlier (SFO) detection aims to discover spatial flows whose non-spatial attribute
values are significantly different from their neighborhoods. Different from spatial flow …

A geographical flow (hereafter flow) is defined as a movement between locations at two
different times. A group of spatiotemporal flows can be viewed as a cluster if their origins and …

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 …