Mining Spatio-Temporal Information Systems
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) will especially 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. An 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.
Mining Spatio-Temporal Information Systems, an edited volume is composed of chapters from leading experts in the field of Spatial-Temporal Information Systems and addresses the many issues in support of modeling, creation, querying, visualizing and mining. Mining Spatio-Temporal Information Systems is intended to bring together a coherent body of recent knowledge relating to STIS data modeling, design, implementation and STIS in knowledge discovery. In particular, the reader is exposed to the latest techniques for the practical design of STIS, essential for complex query processing.
Mining Spatio-Temporal Information Systems is structured to meet the needs of practitioners and researchers in industry and graduate-level students in Computer Science.
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INDEXING OF OBJECTS ON THE MOVE
SUMMARY OF PERFORMANCE EXPERIMENTS
THE GIDB SYSTEM
A FLEXIBLE FRAMEWORK
SPATIOTEMPORAL INFORMATION FOR THE DYNAMIC
INTERACTIVE ACCURATE VISUALIZATION OF NON
QUERYING WITH SPATIOTEMPORAL OPERATIONS
VISUAL QUERY OF TIMEDEPENDENT 3D WEATHER
SCALABLE HIERARCHICAL 3D DATA STRUCTURE
CONCLUSIONS AND FUTURE WORK
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aggregation algorithms analysis application approach attribute binary bounding interval bounding rectangles changes computed convex hull data mining data model data set data types Database Systems defined described developed Digital dimensions Doppler radar dynamic Egenhofer Erwig evolving region example expired entries Extent Figure FNMOC format function Geographic Information Systems geometry geospatial gext GIDB GRIB gridded GŁting histories implementation integration knowledge discovery language bindings lu parcel mesocyclones metadata moving points multirelational NIMA nodes object database ODMG operations parameter quadtree query language R*-tree Range Query relation Relationship Query retrieval space spatial and temporal Spatial BLOB spatial data mining spatial predicates spatial queries spatial subgroups spatio Spatio-Temporal BLOB spatio-temporal data spatio-temporal objects spatio-temporal predicates spatiotemporal information spatiotemporal queries specific storage stored subgroup mining Temporal BLOBs Temporal Databases temporal queries terrain timestamp TPR-tree tree Tripod update values volumetric data weather events