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

The advances in location-acquisition and mobile computing techniques have generated
massive spatial trajectory data, which represent the mobility of a diversity of moving objects …

Owing to the space–air–ground integrated networks (SAGIN), seaborne ship** has
attracted increasing interest in the research on the motion behavior knowledge extraction …

In almost every scientific field, measurements are performed over time. These observations
lead to a collection of organized data called time series. The purpose of time-series data …

Data mining is the discovery of interesting, unexpected or valuable structures in large
datasets. As such, it has two rather different aspects. One of these concerns large …

We investigate techniques for analysis and retrieval of object trajectories in two or three
dimensional space. Such data usually contain a large amount of noise, that has made …

This is the first book to take a truly comprehensive look at clustering. It begins with an
introduction to cluster analysis and goes on to explore: proximity measures; hierarchical …

Existing trajectory clustering algorithms group similar trajectories as a whole, thus
discovering common trajectories. Our key observation is that clustering trajectories as a …

An increase in the size of data repositories of spatiotemporal data has opened up new
challenges in the fields of spatiotemporal data analysis and data mining. Foremost among …

The Definitive Volume on Cutting-Edge Exploratory Analysis of Massive Spatial and
Spatiotemporal DatabasesSince the publication of the first edition of Geographic Data …