Large volumes of spatio-temporal data are increasingly collected and studied in diverse
domains, including climate science, social sciences, neuroscience, epidemiology …

Events are occurrences in specific locations, time, and semantics that nontrivially impact
either our society or the nature, such as earthquakes, civil unrest, system failures …

Anomalies are occurrences in a dataset that are in some way unusual and do not fit the
general patterns. The concept of the anomaly is typically ill defined and perceived as vague …

Explosive growth in geospatial and temporal data as well as the emergence of new
technologies emphasize the need for automated discovery of spatiotemporal knowledge …

Outlier detection is an extensive research area, which has been intensively studied in
several domains such as biological sciences, medical diagnosis, surveillance, and traffic …

Reservoirs supply drinking water to many major cities in China, and their ecological security
ensures the economic development, drinking water safety and ecological balance of cities …

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 …

With the advancement of remote sensing technology, wide usage of GPS devices in vehicles
and cell phones, popularity of mobile applications, crowd sourcing, and geographic …

Over the last decennium, the object detection is the pivotal step in any machine vision and
image processing application. It is the initial step applied to extract most informative pixel …

This paper provides a short overview of space–time series clustering, which can be
generally grouped into three main categories such as: hierarchical, partitioning-based, and …