Clustering has gained widespread use, especially for static data. However, the rapid growth of spatio-temporal data from numerous instruments, such as earth-orbiting satellites, has created a need for spatio-temporal clustering methods to extract and monitor dynamic clusters. Dynamic spatiotemporal clustering faces two major challenges: First, the clusters are dynamic and may change in size, sh...

Currently, there are strong efforts to integrate spatial and temporal database technology into spatio-temporal database systems. This paper views the topic from a more fundamental perspective and makes several contributions. First, it reviews existing temporal and spatial data models and presents a completely new approach to temporal data modeling based on the very general notion of temporal ob...

Generative Adversarial Networks (GANs) have shown remarkable success in producing realistic-looking images the computer vision area. Recently, GAN-based techniques are to be promising for spatio-temporal-based applications such as trajectory prediction, events generation, and time-series data imputation. While several reviews GANs been presented, no one has considered addressing practical chall...

In the paper, we consider the problem of discovering sequential patterns from event-based spatio-temporal data. The problem is defined as follows: for a set of event types F and for a dataset of events instances D (where each instance in D denotes an occurrence of a particular event type in considered spatio-temporal space), discover all sequential patterns defining the following relation betwe...

The notion of spatio-temporal multi-granularity is fundamental when modeling objects in GIS applications in that it supports the representation of the temporal evolutions of these objects. Concepts and issues in multi-granular spatio-temporal representations have been widely investigated by the research community. However, despite the large number of theoretical investigations, no comprehensive...

Integrating spatio-temporal data as abstract data types into already existing data models is a promising approach to creating spatio-temporal query languages. Based on a formal foundation presented elsewhere, we present the main aspects of an SQL-like, spatio-temporal query language, called STQL. As one of its essential features, STQL allows to query and to retrieve moving objects which describ...

The spectacular evolution of sensor networks and the proliferation of location-sensing devices in daily life activities are leading to an explosion of disparate spatio-temporal data. The collected data describes the movement of mobile objects used to construct what we call trajectory data. The diversity of these generated data has led to a variety of spatio-temporal models. In fact, the concept...