A proper understanding of urban functions is fundamental to prevent urban problems and
promote better built environments. While previous studies focus mainly on inferring urban …

This study proposes a new prescriptive analytics method that aims to provide decision-
makers with a systematic and objective approach to identify suitable locations, considering …

The development of information technology has enabled many different technologies to
collect large amounts of spatial data every day. It is of very great significance to discover …

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

Spatial data often exhibit a tendency highly similar to spatial objects located close to each
other. Thus, prevalent co-location pattern (PCP) mining has been studied extensively to …

Extracting useful spatial co-location patterns from urban service facilities can help planners
allocate limited resources effectively. These facilities are mostly distributed within man-made …

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 …

As urban areas expand, understanding the spatial organization of urban functional zones
becomes crucial for efficient urban planning and sustainable growth. The Yangtze River …

Colocation pattern mining finds a set of features whose instances frequently appear nearby
in the same geographical space. Most of the existing algorithms for colocation patterns find …

Creating a cityscape conducive to a safe and efficient pedestrian experience requires a
holistic understanding of the relationship between the built structures of a city and the …