Sensitivity and Uncertainty Analysis Approach for GIS-MCDA Based Economic Vulnerability Assessment

Abstract

This research aims to employ a novel methodology for modelling uncertainty in the GIS environment. The spatially explicit sensitivity and uncertainty analysis was applied on Multicriteria Decision Analysis (MCDA) for an economic vulnerability assessment within the Salzach Basin. The main objective of this research is to demonstrate how a unified approach of uncertainty and sensitivity analysis can be applied to minimize the associated uncertainty within an economic vulnerability assessment. In order to achieve this objective, the following methodology, composed four steps, was applied: (1) computation of criteria weights using Analytic Hierarchy Process (AHP); (2) Monte Carlo Simulation was applied for computing the uncertainties associated with AHP weights; (3) the Global Sensitivity Analysis (GSA) was employed in the form of the model-independent method of output variance decomposition, in which the variability of vulnerability maps is apportioned to every criterion weight, generating one first-order (S) and one total-effect (ST) sensitivity index map per criterion weight; and (4) an Ordered Weighted Averaging method was applied for producing vulnerability maps. The results of this research demonstrated the robustness of spatially explicit GSA for minimizing the uncertainty associated with GIS-MCDA models. According to the achieved results, we conclude that applying the variance based GSA leads to a spatial and statistical assessment of the importance of each input factor on the outcome of the GIS-MCDA method, which allows us to introduce and recommend GIS based GSA as a useful methodology for minimizing uncertainty of GIS-MCDA.

Impacts of the Urmia Lake Drought on Soil Salinity and Degradation Risk: An Integrated Geoinformatics Analysis and Monitoring Approach

“…Leveraging this capability, we employed 14 criteria in four major groups to analyze soil salinity and develop a soil degradation risk map (Figure 3). The relevant criteria were selected based on previous international studies on soil degradation mapping [48,[72][73][74][75][76] as well as earlier local soil research studies [16,19]. We selected criteria that represent the soil characteristics and relevant factors that impact the soil degradation in ULB.…”

Review of GIS Multi-Criteria Decision Analysis for Managed Aquifer Recharge in Semi-Arid Regions

“…Commonly applied techniques for sensitivity analysis include principal component analysis (PCA) (Andreo et al 2008), scaling methods (Kattaa et al 2010), re-assignation of criterion values (Fenta et al 2015;Gdoura et al 2015;Fathi et al 2020), and combination of contrasting suitability classes using an area of interest technique (Fuentes and Vervoort 2020). It is beyond the scope of this review to provide an in-depth description of the various approaches to sensitivity analysis for MAR suitability mapping, and the reader is hence directed to the literature for a comprehensive overview (Malczewski 1999;Delgado and Sendra 2004;Ligmann-Zielinska and Jankowski 2008;Feizizadeh et al 2015).…”