|
Spatial Multi-Criteria Decision-Making Approach in Evaluating Walkability Indices: A Case Study of New York City
|
Sara Jokar   , Mohammad Taleai * , Ehsan Sadooghi |
| K. N. Toosi University of Technology |
|
|
Abstract: (531 Views) |
Given the importance of walking and its impact on the physical and mental health of citizens, various criteria for evaluating walkability in urban areas have been developed in recent years. Walkscore is one of the most recognized and widely used tools in this field. However, this index focuses primarily on access to specific types of destinations and does not encompass the broader dimensions of walkability. Accordingly, this study aims to develop a more comprehensive walkability index by incorporating a wider range of indicators representing different dimensions of walkability, using spatial multi-criteria decision-making methods for weighting and integration. To this end, a set of 24 indicators related to various aspects of walkability was selected. In subsequent steps, three weighting scenarios and two indicator integration methods—TOPSIS and Weighted Linear Combination (WLC)—were applied to perform sensitivity analysis and identify the optimal weighting strategy. The proposed method was then compared with walkability indices developed in previous studies using statistical measures.
Given the importance of walking and its role in promoting the physical and mental well-being of the urban residents, various indices have been developed in recent years to assess walkability in the urban environments. Among these, the Walk Score is a widely recognized tool; however, it primarily focuses on access to some selected services and fails to capture the multifaceted nature of walkability. Accordingly, this study aims to develop a comprehensive walkability index by incorporating a broader range of indicators that reflect its various dimensions, using spatial multi-criteria decision-making methods for weighting and integration. To this end, a set of 24 indicators related to different aspects of walkability were selected. Subsequently, three weighting scenarios and two integration methods—TOPSIS and Weighted Linear Combination (WLC)—were employed to conduct the sensitivity analysis and determine the most effective weighting strategy. The performance of the proposed approach was evaluated using objective assessment methods based on the statistical measures and walkability indices developed in the previous studies. The results indicate that factors such as access to parking lots and public services, land-use mix, street connectivity, residential density, and maximum permissible street speed are among the most influential variables affecting walkability in the study area. Comparative analysis of the scenarios revealed that Scenario 2, which reduces the indicators to 16 using Principal Component Analysis (PCA), reflects a more optimistic approach than Scenario 1, which adopts a pessimistic perspective, while Scenario 3, which reduces the indicators into five principal dimensions, offers a balanced alternative. Furthermore the comparison of the computed indices with the Walk Score map was done. The results showed that the WLC method under Scenario 3, based on the main criteria, aligns more closely with Walk Score than TOPSIS. The results underscore the critical role of weighting and integration strategies in spatial multi-criteria analysis for constructing the effective walkability indices.
|
|
| Keywords: Walkability Index, Spatial Multi-Criteria Decision-Making, Sensivity Analysis, Walkscore |
|
|
Full-Text [PDF 2131 kb]
(39 Downloads)
|
Type of Study: Research |
Subject:
GIS
Received: 2024/07/31 | Accepted: 2025/06/3 | ePublished ahead of print: 2026/01/31 | Published: 2026/04/11
|
|
|
|
|
|
|
| Send email to the article author |
|
|
