Spatial co-location pattern mining is an interesting and important task in spatial data mining
which discovers the subsets of spatial features frequently observed together in nearby …

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 …

The water quality index (WQI) is a widely used tool for comprehensive assessment of river
environments. However, its calculation involves numerous water quality parameters, making …

Spatiotemporal association pattern mining can discover interesting interdependent
relationships among various types of geospatial data. However, existing mining methods for …

With the rapid development of science technology, finding prevalent spatial patterns from
urban facility data has gradually become an important issue in smart city applications. Co …

Statistically clustering air pollution can provide evidence of underlying spatial processes
responsible for intensifying the concentration of contaminants. It may also lead to the …

Co-location patterns refer to subsets of Boolean spatial features with instances of these
features frequently appear in nearby geographic space. Maximal co-location patterns are a …

Real space teems with potential feature patterns with instances that frequently appear in the
same locations. As a member of the data-mining family, co-location can effectively find such …

A spatial co-location pattern is a set of spatial features frequently co-occuring in nearby
geographic spaces. Similar to closed frequent itemset mining, closed co-location pattern …

The increasing air pollution poses an urgent global concern with far-reaching
consequences, such as premature mortality and reduced crop yield, which significantly …