Building a geographical information systems application using Microsfot SQL Server 2008 & Microsoft Bing Maps

Abstract

A geographical information system incorporates various technologies for data capturing, management, manipulation, analysis and visualisation of spatial data. In fact, GIS applications apart handling alphanumeric data, allows manipulation of location-based data for analysis purposes. On the other hand such systems are expensive and complex in nature and require companies to invest not only on the product itself but also on expert personnel to benefit from their analysis processing power and functionalities. Therefore the aim and objectives for this final year project was to investigate the possibility of using new technologies such as Microsoft SQL Server 2008 and Bing maps to design and develop a system which is capable of handling and managing GIS layers, perform data capturing and also provides attributes and spatial querying functionality for data manipulation. The investigation results led to the delineation of requirements and specifications to develop a GIS application incorporating various technologies such as WCF service, Asp.Net Web pages and windows-based application to provide layer management and also spatial data manipulation. Subsequently within this dissertation a description of the methodology used to design and implement these requirements is given. The evaluation process for this final year project was done by outlining three case studies which purpose was to test the system on its overall performance, usability, portability, layer management capabilities, data capturing capabilities, querying power and also an overall comparison with existing commercial GIS applications. The results derived from the evaluation process were of a system capable of accomplishing the criteria delineated above. Hence when looking back to the developed system and also to the outcome of the case studies performed, the system offers a user friendly environment where to build spatial layers and manipulate spatial data through queries without the need to run in extreme costs and also without the need ot expert usag