Spatial location or position information represents an appropriate means for exactly pinpointing an object on Earth. Most of the positioning methods used in the area of LBSs, for example, GPS, deliver spatial location information as a direct result from the measurements of one or several observables and subsequent calculations. However, spatial location is not an intuitive approach that is clearly understood in all situations. For example, delivering a target’s position to the LBS user as N 48◦ 21’ 17” E 11◦ 47’ 15” is less meaningful than the simple statement that the target person currently resides at the airport in Munich, Germany. Similar problems appear when setting two positions in relation, for example, for determining the distance between the LBS user and a selected point of interest and deriving the expected traveling time from that. A simple approach would deliver only the line-ofsight distance between both positions, but it would be more convenient for the user to get the shortest route distance in a road or public transportation network, preferably in combination with the shortest route displayed on a map and additional navigation assistance. As these examples demonstrate, it is inevitable to care for the mapping between spatial and descriptive location information as well as for maintaining and deriving relationships between locations in general.

Spatial databases and Geographic Information Systems (GISs) are the essential key technologies for fulfilling these tasks. While they cover a broad range of applications, for example, in the areas of surveying, mapping, and transportation, in the context of LBSs they are important for indicating the positions of one or several targets with respect to geographical content like borders of cities and countries, road networks, or buildings. They are used for mapping spatial location onto meaningful descriptive location information and vice versa, which is referred to as geocoding and reverse geocoding respectively, as well as for creating digital maps and routing information, or for finding nearby points of interest.

This chapter gives a general overview of spatial databases and GISs as it is necessary for the understanding of LBSs, rather than providing an in-depth knowledge of all related background technologies, research and related challenges, or even concrete products. Starting with a definition of spatial databases and GIS, the chapter explains the underlying data models and shows how to represent spatial objects and topological relationships. It introduces the three common database approaches GISs rely on and the concept of features and themes. Furthermore, the method for querying geographic content and relating it with the position data of LBS targets is demonstrated by an example. Finally, the chapter concludes with an overview of the algorithms of computational geometry and an introduction to the Geography Markup Language (GML).

Contents

• What are Spatial Databases and GIS?
• Geographic versus Spatial Data Models
• Representing Spatial Objects
  • Raster Mode
  • Vector Mode
  • Representing Topological Relationships
  • Database Approaches for Spatial Objects
• Features and Themes
  • Conceptual Schemes
  • Operations
  • Topological Predicates
  • Queries
• Algorithms of Computational Geometry
• Geography Markup Language
• Conclusion