With the development of information and communications technology, user-generated
content and crowdsourced data are playing a large role in studies of transport and public …

A bivariate flow cluster is a group of two types of spatial flows, where both types of flows
have high (or low) values, or one type of flow has a high value while the other has a low …

This study aims at developing a data‐driven and bottom‐up spatial statistic method for
identifying regions of anomalous spatial interactions (clusters of extremely high‐or low …

Hotspot detection is an important exploratory technique to identify areas with high
concentrations of crime and help deploy crime-reduction resources. Although a variety of …

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

Identifying anomalies from geochemical data by modeling of the background and statistical
evaluation of anomalies is a major concern in geochemical exploration. This study …

This study compared three local cluster detection methods to identify local hotspots of
human cutaneous anthrax (HCA) transmission in the country of Georgia where cases have …

The globalisation era in which we live has made the world an interconnected space with
several global trends. We find developing countries with very high growth rates, what helps …

Environmental local agencies have to enforce European directives that impose a land
classification, according to air quality status, to distinguish zones needing further actions …

We compared a local clustering and a cluster morphology statistic using anthrax outbreaks
in large (cattle) and small (sheep and goats) domestic ruminants across Kazakhstan. The …