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1 April 2013 Spatial uncertainty analysis in coastal land use planning: a case study at Gold Coast, Australia
Razieh Mosadeghi, Jan Warnken, Hamid Mirfenderesk, Rodger Tomlinson
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Abstract

Mosadeghi, R., Warnken, J., Mirfenderesk, H., Tomlinson, R., 2013. Spatial uncertainty analysis in coastal land use planning: a case study at Gold Coast, Australia.

Vulnerability of coastal areas to the global environmental changes and uncertainties in climate change predictions, particularly at local scales has presented a challenge to land-use planning in coastal cities. To make more accurate decisions, the uncertainty due to imperfect knowledge (epistemic uncertainty) is required to be considered in tandem with the inherent uncertainty or randomness of nature, and socio-economic dynamics (stochastic uncertainty). This paper examines the application of spatial Multi-criteria Decision Making (MCDM) tools to evaluate the effects of uncertainties at each stage of the decision- making process. The north east Gold Coast, Queensland (Australia) was considered as a case study to evaluate the sensitivity of the land-use planning decisions to input uncertainties. Uncertainty analysis in the framework of MCDM has been performed to address epistemic uncertainty. To examine the effects of uncertainty in a spatial context, conventional uncertainty analysis was combined with the visualisation capability of GIS and Monte Carlo simulation algorithm. The analysis results graphically display the sensitivity of output to the uncertainties in inputs and present a promising way to assist more transparency in the decision-making process.

Razieh Mosadeghi, Jan Warnken, Hamid Mirfenderesk, and Rodger Tomlinson "Spatial uncertainty analysis in coastal land use planning: a case study at Gold Coast, Australia," Journal of Coastal Research 65(sp1), 1003-1008, (1 April 2013). https://doi.org/10.2112/SI65-170.1
Received: 7 December 2012; Accepted: 6 March 2013; Published: 1 April 2013
KEYWORDS
GIS
Monte Carlo simulation
Multi-criteria decision making
sensitivity analysis
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