Relational Database Framework for Geo Spatial Data Sets

Abstract

Geographic Information Systems (GISs) have emerged as the most powerful and effective decision-making tools in terms of gathering, analysis, interpreting, distribution and using geographically referenced (Spatial) data for use in a wide variety of application domains, such as urban planning, natural resource management, telecommunication network management, vehicle navigation, etc. GIS now embraces a broad range of disciplines including Surveying and Mapping, Remote Sensing (RS), Global Positioning Systems (GPS) among others. However, the main drawback of GISs is the weak link with Relational Database Management Systems (RDBMS) because present day Geospatial databases are file based. Without formal mechanisms for data sharing, much time and resources are wasted in duplication of efforts and digital data conversion processes. The relational model is the predominant and well-established data model, which is used to implement many commercial relational DBMS packages and application systems. This dissertation presents principles, methods and mechanisms for the development of GeoSpatial Databases based on the relational database model. The research also presents a relational database framework that accommodates geospatial data sets and algorithms for spatial data analysis. The research proposes relational algebra extensions to include these spatial functions before. This thesis will ultimately lay the foundation for the development of fully relational geospatial database systems.