The Springer International Engineering and Computer Science

We are facing a rapidly growing capability to collect more and more data regarding our environment. With that, we must have the ability to extract more insightful knowledge about the environmental processes at work on the earth. Spatio-temporal information systems (STIS) should prove beneficial in producing useful knowledge about changes in our world from these ever-burgeoning collections of environment data. STIS provide the ability to store, analyze and represent the dynamic properties of the environment, that is, geographic information in space and time. A STIS, for example, can produce a weather map, but more importantly, it can present a user with information in map or report form indicating how precipitation progresses in space over time to affect a watershed. Other uses include forestry and even electrical systems management. Forestry experts using an STIS are able to examine the rates of movements of forest fires, how they evolve over time, and their impact on forest growth over long periods of time. A large electrical network system manager uses an STIS to track the failures and repairs of electrical transformers. Use of an STIS in this case allows the reconstruction of the status of the network at any given past time. This title is an edited volume is composed of chapters from experts in the field and addresses the many issues in support of modelling, creation, querying, visualizing and mining. The book is intended to bring together a coherent body of knowledge relating to STIS data modelling, design, implementation and STIS in knowledge discovery. In particular, the reader is exposed to the most up-to-date techniques for the practical design of STIS, essential for complex query processing. It is structured to meet the needs of practitioners and researchers in industry and graduate-level students in computer science.