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  • 标题:Sensitivity and Uncertainty Analysis Approach for GIS-MCDA Based Economic Vulnerability Assessment
  • 本地全文:下载
  • 作者:Bakhtiar Feizizadeh ; Stefan Kienberger ; Khalil Valizadeh Kamran
  • 期刊名称:GI_FORUM - Journal for Geographic Information Science
  • 电子版ISSN:2308-1708
  • 出版年度:2015
  • 页码:81-89
  • DOI:10.1553/giscience2015s81
  • 出版社:ÖAW Verlag, Wien
  • 摘要:This research aims to employ a novel methodology for modelling uncertainty in the GISenvironment. The spatially explicit sensitivity and uncertainty analysis was applied onMulticriteria Decision Analysis (MCDA) for an economic vulnerability assessment withinthe Salzach Basin. The main objective of this research is to demonstrate how a unifiedapproach of uncertainty and sensitivity analysis can be applied to minimize the associateduncertainty within an economic vulnerability assessment. In order to achieve this objective,the following methodology, composed four steps, was applied: (1) computation of criteriaweights using Analytic Hierarchy Process (AHP); (2) Monte Carlo Simulation was appliedfor computing the uncertainties associated with AHP weights; (3) the Global SensitivityAnalysis (GSA) was employed in the form of the model-independent method of outputvariance decomposition, in which the variability of vulnerability maps is apportioned toevery criterion weight, generating one first-order (S) and one total-effect (ST) sensitivityindex map per criterion weight; and (4) an Ordered Weighted Averaging method was appliedfor producing vulnerability maps. The results of this research demonstrated the robustnessof spatially explicit GSA for minimizing the uncertainty associated with GISMCDAmodels. According to the achieved results, we conclude that applying the variancebased GSA leads to a spatial and statistical assessment of the importance of each inputfactor on the outcome of the GIS-MCDA method, which allows us to introduce and recommendGIS based GSA as a useful methodology for minimizing uncertainty of GISMCDA.
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