Spatial and temporal properties are key aspects of many data analysis problems in business, government, and science. GPS technology is quickly enabling a number of new applications, including tracking fleets of vehicles, navigating boats and ships, pedestrian's tracking and tracking of wildlife. Another popular application of this technology is in cellular phones with embedded GPS sensors for vehicle and pedestrian's tracking. Through the availability of cheap sensor devices, we have witnessed an exponential growth of geo-tagged data in the last few years resulting in the availability of fine-grained spatial data at small temporal sampling intervals. Therefore, the actual challenge in spatio-temporal analysis is moving from acquiring the right data towards large-scale analysis of the available data. As this multidimensional data add more complexities in storing, indexing and querying, efficient methodologies have to be derived to manage these data using existing data base technology.