Forest fire susceptibility mapping via multi-criteria decision analysis techniques for Mugla, Turkey: A comparative analysis of VIKOR and TOPSIS

2021 ◽  
Vol 480 ◽  
pp. 118644
Author(s):  
Fatih Sari
CATENA ◽  
2019 ◽  
Vol 180 ◽  
pp. 282-297 ◽  
Author(s):  
Alireza Arabameri ◽  
Biswajeet Pradhan ◽  
Khalil Rezaei ◽  
Christian Conoscenti

2020 ◽  
pp. 652-664
Author(s):  
Kesra Nermend ◽  
Mateusz Piwowarski ◽  
Mariusz Borawski

In this study different methodological approaches are used and described by many features (indicators) of complex socio-economic process. Outcome of analysis has the most reliable and acceptable representation of the studied process specific to chosen case. In order to solve problems in this area (depending on the situation, case under consideration), methods from two groups are most often used: multidimensional comparative analysis and multi-criteria decision analysis. The first of these cases concern problems at the macro level (socio-economic development, demographic situation, population's living standards, etc.), in which the decisionmaker's participation is relatively small (eg the selection of diagnostic variables or expert assessment). The second of these groups include issues in which the decisionmaker's participation is significant which are subjective to the decisions taken and reflects his or her preferences. Among the decision support methods, one can also distinguish those that have both the characteristics of methods from the area of multidimensional comparative analysis and multi-criteria decision analysis. The article presents the combination of both trends exposing maximum possibilities of using selected methods used in the decision making by Polish schools. The general methodological assumptions, advantages of having approaches discussed (in relation to other known methods) as well as the applied aspects (exemplary applications) also presented.


2020 ◽  
Vol 7 (1) ◽  
pp. 1776451 ◽  
Author(s):  
Pablo César Manyoma-Velásquez ◽  
Carlos Julio Vidal-Holguín ◽  
Patricia Torres-Lozada

2021 ◽  
Author(s):  
Anna Racovali

This paper explores alternative methods in which an urban walkability score may be determined. Walk Score is a popular urban accessibility index which determines the walkability of a neighbourhood or specific address by measuring the proximity of the location to nearby services and amenities. Traditional walkability scores, such as Walk Score, are limited because of their inability to vary the importance of being in proximity to certain services and amenities. Multi-criteria decision analysis (MCDA) techniques, specifically simple additive weighting (SAW) and ordered weighted averaging (OWA), provide a geographic approach to determining the walkability of an area and allow users to determine the weights of importance of all services and amenities. MCDA-based walkability scores were calculated and compared to one another and to Walk Score. Both SAW and OWA methods created similar walkability indexes for dissemination areas throughout Toronto. However, the MCDA results could not be directly compared to Walk Score, as there was a significant difference between the value ranges of the scores. Thus, the 140 Toronto neighbourhoods were ranked from most to least walkable for the MCDA-based methods and Walk Score, based upon each method’s respective scores. Upon comparison, it was evident that both Walk Score’s methodology and the MCDA-based methodologies resulted in similar outcomes of walkability rankings for Toronto neighbourhoods


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