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

Understanding population density at a fine spatial scale is beneficial for urban management
and planning. Existing machine learning methods have been widely used to predict the …

Tailings dams in mining areas frequently experience the phenomenon of haphazard
dumping and stacking of a large amount of tailings waste. Under the influence of surface …

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 …

Urban geographical environments play an important role in inducing the occurrences of
street crimes, so they have raised attention regarding the relationships between …

Using individual-level data collected from two communities in Hong Kong, this study
proposes a significant association rule mining method to identify the complex associations …

Bivariate association analyses of spatial flows can reveal the spatial dependence of two
types of spatial flows. However, existing studies involving the detection of the bivariate …

Water quality prediction in the spatially heterogeneous environment is challenging as the
importance of water quality parameters (WQPs) and the performance of prediction models …

High-speed information technology development has made virtual social networking (VSN)
a social interaction trend. Studies have been carried out to investigate the spatial clustering …

Spatial association rule mining can reveal the inherent laws of spatial object
interdependence and is an important part of spatial data mining. Most of the existing …