Multi-criteria risk evaluation by integrating an analytical network process approach into GIS-based sensitivity and uncertainty analyses

Abstract

Geographic information system (GIS)-based multi-criteria decision analysis (MCDA) is commonly used to solve a range of complex spatial problems. We have incorporated an analytical network process (ANP) as a central part of MCDA and used this approach for land subsidence susceptibility mapping (LSSM). We used an ANP approach in combination with the concepts of global sensitivity and uncertainty analyses, in order to minimize any associated errors. This approach was tested for a LSSM application in northwestern Iran, using a methodology that consisted of three distinct phases. An ANP approach was used in the first phase to derive criteria weightings by analysing relevant criteria, which included topographic, hydrologic, climatologic, geological, and anthropological indicators. The second phase involved evaluating the uncertainty and sensitivity of areas susceptible to subsidence as a function of the derived weightings, using Monte Carlo simulations. The third phase then used a land subsidence inventory database to validate the results and to measure any improvement in accuracy following sensitivity analysis. Results indicated a 6% improvement in the accuracy of the ANP method as a result of using an integrated global sensitivity analysis.

Sustainable Urban Transport Planning Considering Different Stakeholder Groups by an Interval-AHP Decision Support Model

“…In order to deal with these issues, many studies have aimed at reducing the amount of inherent uncertainty associated with the AHP method. There are some studies that have suggested the use of sensitivity and uncertainty analyses and integration of the AHP with statistical approaches such as the Monte Carlo simulation [38,39]. The fuzzy-AHP is based on different membership functions that are considered to be an effective and flexible technique in some cases [40].…”

Assessment of irrigation water quality by a Geographic Information System–Multicriteria Decision Analysis‐based model: A case study from Ankara, Turkey

“…The authenticity of spatial simulation models and GIS‐MCDA techniques depend on how the relative importance of each criteria has been calculated (Ghorbanzadeh, Feizizadeh, & Blaschke, ). The personal preferences of decision maker in determining the criteria weights directly affect the accuracy of model because the decision maker's individual preferences are assumed to be actual rules in the decision‐making process (Ghorbanzadeh et al, ). AHP and DEA methods are commonly used in the literature for choosing the best alternative and to determine the weights of alternatives and criteria.…”

A new GIS-based data mining technique using an adaptive neuro-fuzzy inference system (ANFIS) and k-fold cross-validation approach for land subsidence susceptibility mapping

“…From a geological point of view, the study area coincides with the same lithological formation, namely a high level piedmont fan and valley terrace deposits Q ft1 belonging to the Quaternary age (Khaleghi and Shahverdizadeh 2014). The primary local activity is agriculture, including irrigated and rain fed agriculture and orchards (Khorrami 2016;Ghorbanzadeh et al 2017). Agriculture in the region requires a huge amount of surface and underground water.…”

“…Lee et al (2012) assessed ground subsidence susceptibility (GSS) in South Korea using artificial neural networks (ANN). A GIS-MCDA method was also used by Ghorbanzadeh et al (2017) to identify areas that are prone to land subsidence in the Marand plain, while Dehghan-Soraki et al (2015) applied ASAR and PALSAR data to analyze and measure the land surface change rates caused by subsidence. Karimzadeh et al (2013) and Karimzadeh (2015) used the same type of data in order to distinguish the surface deformation in another basin in the Northwest of Iran.…”