This course introduces fundamental ideas underlying geo-spatial science, systems and services. These include spatial concepts and data models, spatial query languages, spatial storage and indexing, query processing and optimization, spatial networks and spatial data mining.
1. The student is able to distinguish between traditional relational data and spatial data by pointing out some of the unique challenges of handling spatial data. For example, by being able to defend the need for operators beyond the traditional select, project and join of traditional relational databases.
2. The student is able to define and interpret basic terminology of spatial data, e.g., field vs object data models, field operators, OGIS operators, spatial query languages, index structures for spatial data etc.
3. The student is able to apply basic spatial query processing algorithms such as Voronoi diagrams, convex hulls, and search algorithms on spatial index structures.
4. The student is also able to apply basic spatial data mining algorithms such as co-location and hotspot detection.