International Journal of Geographical Information Systems · 2006 · 115 citations · 38 references
ComputingEnvironmental EngineeringEnvironmental ManagementGeographic Information SystemsHazardous Waste ManagementSpatial AnalysisDisposal FacilitiesLandfill ManagementLocation AnalysisSensitivity AnalysisDisposal Site SelectionGeographic Information Systems (Gis)Gis-based OptimizationGlobal Sensitivity AnalysisMulticriteria Decision AnalysisNumerical ModellingSensitivitySensitivity Indices
Global sensitivity analysis has proven useful in numerical modelling applications. The study presents a novel application of sensitivity analysis by jointly using GSA, GIS, and multi‑criteria evaluation to plan hazardous waste disposal. The authors applied Sobol' and E‑FAST variance‑based methods to 11 factors in a GIS‑based case study, then simplified the model to the three most influential factors. Only three factors explain 97 % of the output variance, enabling the study to infer results from a pilot area to the entire region and optimize GIS data acquisition resources.
A novel application of Sensitivity Analysis is presented. Useful applications of Global SA (GSA) already exist in the field of numerical modelling. In this paper, we explore the joint use of GSA, Geographical Information Systems (GIS) and Multi‐Criteria Evaluation. In this preliminary case study, 11 factors have been used to find the best place to locate a hazardous waste landfill. Two variance‐based methods (Sobol' and E‐FAST) are used to compute sensitivity indices in order to identify the factors that determine the variance of the model output. The results show that only three factors jointly account for 97% of the output variance. This information is employed to make a simplification of the original model, retaining only these three influential factors. In addition, if the SA is carried out in a pilot area where the spatial properties are similar to those of the whole region, we can infer the results to the whole area. This procedure achieves the goal of the study with an optimized allocation of resources for GIS data acquisition.
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Photogrammetric Engineering and Remote Sensing
John Nicol, B. King · UCL Discovery (University College London) · 2007 · 9.4K citations
GIS and Multicriteria Decision Analysis
C. Leake, Jacek Malczewski · Journal of the Operational Research Society · 2000 · 3.1K citations