Abstract
Spatial databases have been an active area of research for over a decade, addressing the growing data management and analysis needs of spatial applications such as Geographic Information Systems (GIS). This research has produced spatial data types and operators, spatial query languages and processing techniques, spatial indexing and clustering techniques. In addition, this research also resulted in several extensions to the traditional relational database systems like extensible indexing and extensible optimizers. This database technology made it possible to provide location-based services to web and mobile applications using standard databases. In this paper, we outline some of the features of a spatial database and show how a mobile location-aware application can be supported using the spatial database services.
Introduction
Spatial database management systems aim to make spatial data management easier and more natural to users or applications such as urban planning, utilities, transportation, and remote sensing. Even though traditional database technology has been evolving for the last thirty years, managing spatial data with database system poses many challenges. Databases are traditionally used in business and administrative applications. In such applications the common data types encountered are integer, float, character, monetary-unit and date. And the type of operations performed on these data types are simple arithmetic and logical operations like addition, subtraction, less than, greater than, etc. This limited set of data types and operations makes the modeling of real-world spatial applications extremely difficult. Hence, the recent research in database systems has focussed on efficiently storing and managing complex data like the spatial data. In this paper, we discuss how these new relational databases can be used to solve the problems posed by spatial data management.
A common example of spatial data can be seen in a road map. A road map is a two dimensional object that contains points, lines, and polygons that can represent cities, roads, and political boundaries such as states or provinces. A road map is a visualization of geographic information. The location of cities, roads, and political boundaries that exist on the surface of the Earth are projected onto a two-dimensional display or piece of paper, preserving the relative positions and relative distances of the rendered objects. The data that indicates the Earth location (latitude and longitude, or height and depth) of these rendered objects is the spatial data. When the map is rendered, this spatial data is used to project the locations of the objects on a two-dimensional piece of paper. A GIS is often used to store, retrieve, and render this Earth-relative spatial data. Other types of spatial data include data from computer-aided design (CAD) and computer-aided manufacturing (CAM) systems.
These applications all store, retrieve, update, or query some collection of features that have both non-spatial and spatial attributes. Examples of non-spatial attributes are name, soil_type, landuse_classification, and part_number. The spatial attribute is a coordinate geometry, or vector-based representation of the shape of the feature. The spatial attribute, referred to as the geometry, is an ordered sequence of vertices that are connected by straight-line segments or arcs. The semantics of the geometry is determined by its type, which may be one of point, line string, or polygon.
What are Spatial Databases?
GIS applications today usually store the spatial data and non-spatial or attribute data separately. These systems store spatial data describing the spatial properties of objects in files managed by a file management system. GIS applications then store the attribute data of these objects in a commercial database (like a Relational Database). This split data model has several drawbacks, as it is difficult to maintain data integrity between the spatial data and the attribute data, as the two data are not managed by the same database engine. The ideal solution is an information infrastructure that includes a single database system for managing spatial data, with a data structure that is independent of the application. There are several benefits to managing the spatial and attribute data in a single database. Key benefits of this approach to spatial data management include:
- Better data management for spatial data. Traditional GIS users gain access to complete spatial information system based on industry standards with an open interface to their data (i.e., SQL).
- Spatial data is now stored in enterprise wide DBMS, making it possible to spatially enable many enterprise applications.
- Reduces complexity of systems management by eliminating the hybrid architecture of GIS data models.
- Allows for the seamless integration of
MIS and GIS data stores, delivering applications that meet the
increasingly demanding analysis and reporting needs of a growing
geospatial user community.