Infrastructure Engineering - Research Publications
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ItemThe role of institutional mechanisms in spatial data infrastructure development that supports decision-making(Australian Institute of Cartographers, 2002-01-01)Improved economic, social and environmental decision-making are principal objectives for investing in the development of Spatial Data Infrastructure (SDI) at all political and administrative levels. Indeed, Resolution 7 of the recent 5th Global Spatial Data Infrastructure (GSDI) conference in Cartagena, Colombia (GSDI, 2001) argued that the purpose of the GSDI is to improve the availability, accessibility, and applicability of spatial information for decision-making. While accepting the development of institutional mechanisms to support decision-making by promoting the availability and accessibility of spatial information as part of SDI institutional frameworks, many institutional mechanisms fall short of addressing the application of spatial data to decision-making. From an institutional perspective, the motivation for SDI implementation is the impracticality of a single organisation producing and maintaining the wide variety of data and models needed to inform many decisions, resulting in a need for sharing of data and a range of analytical and display tools. This is being seen particularly in the natural resource, environment and government sectors in Australia. These sectors are utilising institutional mechanisms to support spatial decision-making processes in a number of different ways including the development of community resource centres, departmental development of decision support tools, as well as the development of atlases, spatial data directories and on-line land information services. In Australia these institutional mechanisms are playing a crucial role in providing the building blocks for the institutional framework of SDIs and address different levels of the decision-making process. This paper looks at how availability and accessibility of spatial data are being achieved by reviewing examples from each of the institutional mechanisms mentioned. The variety of decision-making levels supported by these different initiatives is reviewed in terms of decision process theory. The paper concludes with a discussion of the implications of the approaches to developing institutional support for decision-making as part of SDI development, as well as a consideration of directions for SDI development in the future to support spatial decision-making processes.
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ItemSDI development to support spatial decision-making( 2002)Improved economic, social and environmental decision-making are principal objectives for investing in the development of spatial data infrastructure (SDI) at all political and administrative levels. So much so, resolution 7 of the recent 5th Global Spatial Data Infrastructure (GSDI) conference in Cartagena, Colombia argued that the purpose of the GSDI is to improve the availability, accessibility, and applicability of spatial information for decision-making (GSDI 2001). Developing institutional support for decision-making that promotes and incorporates the availability and accessibility of spatial information therefore plays an important role in SDI implementation. From an institutional perspective the motivation for SDI implementation is driven by the impracticality of a single organisation producing and maintaining the wide variety of data and models needed to inform many decisions, which results in increased sharing of data, information, analytical, display and modelling tools. This is being seen particularly in the natural resource, environment and local government sectors in Australia (Feeney et al. 2002). These sectors are utilising a variety of institutional mechanisms in their development of spatial decision support capabilities, which are moving progressively towards models that support the development and availability of interoperable digital geographic data and technologies to support spatial decision-making at different levels and participation. The inclusion of technology support as part of developing SDIs has been recognised as essential to meeting the needs of the multi-disciplinary and multi-participant environments that characterise decision-making for sustainable development (Agenda21 1993, GSDI 2001, Rio+10 2002). Unless a diversity of decision support mechanisms are going to be incorporated more into decision processes many relevant and useful spatial datasets and technologies are not going to be used to their potential to support sustainable development. Government has a central role to play in developing infrastructure that supports the discovery, access and applications of spatial information and technologies for such decision support. This paper looks at a variety of institutional mechanisms, for supporting the decision process, being employed in SDI development in the natural resource and environmental sectors in Australia. The decision-making levels supported by these different mechanisms will be reviewed in terms of organisational decision-making and decision process theories, as well as the level of coordination between institutional approaches at the spatial data policy level. The paper will conclude with a discussion of the implications of the approaches to developing institutional support for decision-making, as part of SDI development, as well as a consideration of directions for SDI development in the future to support spatial decision-making.
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ItemSpatial and temporal representation of environmental policy outcomes using geocomputation: a case study in Victoria, Australia( 2003)For more than 30 years, cost-benefit analysis (CBA) has been used in many countriesas an important tool for evaluating public policies. In most cases CBA uses Kaldor-Hicks theory, which assumes that all the entities in the analysis should be consideredequal when distributing benefits and costs. However, for environmental policyevaluations, and especially for cases where a policy is directly affecting a communityor ecosystem with a high degree of vulnerability, the Kaldor-Hicks theory may not bein concordance with principals of equity and sustainability. In order to incorporatethese two concepts in the Cost-Benefit Analysis, a new approach to presentation ofenvironmental indicators for decision-making is proposed. The use of spatio-temporalenvironmental and social indicators provides the decision-maker with a broaderpicture of positive and negative impacts of the policy by considering entities in theanalysis in a differential form, according to their location in the space-time. A geocomputational(GC) system, which incorporates a space-time model and a geographicinformation system (GIS), was created and designed to generate new representationsof environmental policy outcomes. The system, which could be considered as adecision support system, has been designed to promote discussion in the decisionprocess rather than as a technocratic tool. The indicators and computer-based systemhave been tested in a water resources case study with long-term impacts over a largearea of south-eastern Australia.
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ItemGeo-computational alternative to improve economic evaluation of public policies( 2003)For more than 30 years, cost-benefit analysis (CBA) has been used in manycountries as an important tool for evaluating public policies. In most casesCBA uses Kaldor-Hicks theory, which assumes that all the entities in theanalysis should be considered equal when distributing benefits and costs.However, for environmental policy evaluations, and especially for cases wherea policy is directly affecting a community or ecosystem with a high degree ofvulnerability, the Kaldor-Hicks theory may not be in concordance withprincipals of equity and sustainability. In order to incorporate these twoconcepts in the Cost-Benefit Analysis, a new approach to presentation ofenvironmental indicators for decision-making is proposed. The use of spatiotemporalenvironmental and social indicators provides the decision-maker with a broader picture of positive and negative impacts of the policy byconsidering entities in the analysis in a differential form, according to theirlocation in the space-time. A geo-computational (GC) system, whichincorporates a space-time model and a geographic information system (GIS),was created and designed to generate new representations of environmentalpolicy outcomes. The system, which could be considered as a decisionsupport system, has been designed to promote discussion in the decisionprocess rather than as a technocratic tool. The indicators and computer-basedsystem have been tested in a water resources case study with long-termimpacts over a large area of south-eastern Australia.