scholarly journals Exploring urban accessibility scores using multi-criteria decision analysis techniques

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

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


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

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

2017 ◽  
Vol 59 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Joram Schito

AbstractIn planning transmission lines with the use of Geographic Information Systems, the use of the Least Cost Path (LCP) algorithm has been established while relevant criteria are modeled using Multi-Criteria Decision Analysis (MCDA). Despite their established use, this combination (MCDA/LCP) often leads to results that do not correspond to realistic conditions. Therefore, the MCDA/LCP computation must usually be optimized on an algorithmic level as well as on the decision model and the underlying data relevant for the MCDA. The current paper presents the state-of-the-art of an ongoing research project that aims to solve these issues. First results are promising since a stable algorithm has been developed that computes a cost surface, a Least Cost Corridor (LCC), a LCP, and the transmission towers' positions by simple additive weighting based on user's weights. Optimizations on the MCDA models have already been implemented and tested. The findings are integrated into a 3D Decision Support System which aims at facilitating the work of TL planners by realistic modeling and by reducing the approval process for new TL.


Cities ◽  
2018 ◽  
Vol 72 ◽  
pp. 102-114 ◽  
Author(s):  
Yasser Ebrahimian Ghajari ◽  
Ali Asghar Alesheikh ◽  
Mahdi Modiri ◽  
Reza Hosnavi ◽  
Morteza Abbasi ◽  
...  

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