Develop a Spatial Decision Support System Based on Service-Oriented Architecture

Abstract

A Spatial Decision Support System refers to a computer system that assists decision-makers to generate and evaluate alternative solutions to semi-structured spatial problems through integrating analytical models, spatial data and traditional geoprocessing software so that individuals or groups can make feasible decisions (Armstrong 1993; Densham 1991; Malczewski 1996). It can allow easier decision-making by providing an easy access to geospatial data and analytical models. Many Spatial Decision Support Systems (SDSSs) have been developed for environmental and natural resources decision-making in recent years (e.g., Carver 1999; Jankowski et al, 1997, 2001, 2006; Van Der Perk et al., 2001). However, an important limitation of the SDSS applications is that they are not interoperable. The geospatial data and geoprocessing resources distributed by them cannot be shared and interoperated. While there is an increase in the number of SDSS applications over the past two decades, most of them did not take advantage of the Internet’s distributed nature by sharing spatial data and geoprocessing software (Ostlander 2004; Rinner 2003). Several issues prevent the further development of SDSS applications. One issue is that most SDSSs were developed independently of one another and they are typically standalone systems incapable of sharing and reusing existing data and processing functions. They have their own proprietary system designs, database storage structures, and process models. Thus, it is difficult to communicate and exchange spatial information among these systems, and decision-makers usually cannot integrate data and geoprocessing resources from these systems. Instead of direct integration, they have to spend a lot of money and time on taking a complex procedure to convert the heterogeneous information together. The integration of data and modelling software from disparate sources was beyond the technological capabilities of many potential users (Sengupta & Bennett 2003). The second issue is the duplication problem caused by current SDSSs’ incapability of sharing and reusing existing data and geoprocessing. Because of the lack of interoperability, accessibility and availability of data and information, redundant efforts are commonplace in the development of SDSS applications. While there is a massive increase in the number of SDSS applications over the past two decades, it is often the case that these applications were built with little knowledge of other applications with which they could share information. As a result, many agencies and companies are trying to maintain the databases and