Developing Spatial Data Infrastructures to Facilitate Industrial and Mining Decision-Makings
Source TitleProceedings, Geomatics Seminar, Ministry of Industries and Mines
University of Melbourne Author/sRajabifard, Abbas
AffiliationEngineering: Department of Geomatics
Document TypeConference Paper
CitationsRajabifard, A. (2004) Developing Spatial Data Infrastructures to Facilitate Industrial and Mining Decision-Makings, in Proceedings, Geomatics Seminar, Ministry of Industries and Mines, Tehran, Iran.
Access StatusOpen Access
A preliminary step toward achieving decision-making for complex problems has been increasing recognition of the role of spatial information to generate knowledge, provide added value to identify problems, assist in proposing alternatives and defining a course of action, information discovery, access and use (Williamson et al., 2003). The importance of spatial information to support decision-making and management of growing national, regional, and global issues, such as deforestation and pollution, was specifically cited in the 1992 Rio Declaration on Environment and Development and has been made one of the key themes in subsequent meetings of the Commission on Sustainable Development (CSD, 2001). Since the Rio Declaration call to develop strategies to guarantee the existence of all life, not just human life, there has been acknowledgement of the need to integrate environmental and developmental aspirations at all levels of decision-making.Decision problems that involve spatial data and information are referred to as spatial decision problems. Spatial decision problems often require that a large number of feasible alternatives be evaluated on the basis of multiple criteria, thus spatial decisions are multi-criteria in nature (Massam, 1980). Multi-criteria decision-making is more complex than that based on a single criterion, because of the difficulty finding an alternative that dominates all others with respect to all criteria. The number of people involved in the decision-making process also influences the complexity of spatial decision problems (Massam, 1988). Spatial decision problems may be characterised by different preferences with respect to the decision consequences and the relative importance of the evaluation criteria. The incorporation of values and preferences into decision-making models is an important function of multi-criteria analysis in complex decision problems, and often requires the aid of sophisticated technologies to structure the decision pr
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