Urban and Regional Development Planning
Omid Mazreati Tajabadi; Pooyan Shahabian; Jamaleddin Honarvar
Abstract
Walking constitutes a fundamental activity and pedestrians play a vital role in the vitality of urban spaces. This research endeavor aims to conduct a comparative analysis of walkability between Tehran's Takhti and Marzdaran neighborhoods while validating the findings and comparing specialized ...
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Walking constitutes a fundamental activity and pedestrians play a vital role in the vitality of urban spaces. This research endeavor aims to conduct a comparative analysis of walkability between Tehran's Takhti and Marzdaran neighborhoods while validating the findings and comparing specialized models. The assessment of data and the comparative examination of the two neighborhoods were carried out utilizing three quantitative models: WalkScore, Smartraq, and SpaceSyntax. Statistical analysis was conducted using SPSS LISREL software. The research methodology employed was descriptive, analytical, and survey-based, representing an applied approach. The statistical population encompassed 250 residents from both neighborhoods. The analysis of pedestrian circulation models revealed that the Takhti neighborhood attained a WalkScore rating of 93.07%, achieved a connectivity index of 1.76 in the Space Syntax model, and exhibited three positive Z-scores in the Smartraq model. Conversely, the Marzdaran neighborhood obtained a WalkScore rating of 77.86%, recorded a connectivity index of 1.69 in the Space Syntax model, and displayed three negative Z-scores in the Smartraq model. By evaluating these outcomes and subjecting them to statistical analyses, encompassing the examination of performance, physical, social, and environmental criteria, it becomes evident that the Takhti neighborhood, with an average score of 3.52, exhibits a superior capability for walkability compared to the Marzdaran neighborhood, which achieved an average score of 2.40. These results reinforce the quantitative model findings regarding walkability in the Takhti neighborhood.
Introduction
The absence of pedestrian presence in local areas and the subsequent decline in neighborhood walkability have adverse effects on security, safety, and social interactions. These issues are further compounded by environmental concerns like air and noise pollution, public health implications, anonymity of neighborhood spaces, a lack of community belonging, and the resulting physical fatigue. Therefore, obtaining a comprehensive understanding of the current situation is vital for informed decision-making. To address these challenges, it is crucial for urban designers and planners to evaluate and measure the walkability of neighborhoods. This enables them to transform the urban environment, creating a pedestrian-friendly atmosphere that enhances the quality of walking in cities today. This research aims to assess and analyze the local walkability in two neighborhoods in Tehran, employing the WalkScore, Smartraq, and space syntax methods. By comparing the outcomes of these approaches, the study provides a comprehensive analysis of the walkability status within the selected neighborhoods. Furthermore, the research employs statistical analysis to validate the findings obtained from these models. This rigorous examination ensures the reliability and accuracy of the results. Ultimately, the study will propose recommendations that not only highlight the advantages and limitations of the utilized models but also present a neighborhood pattern that prioritizes pedestrian needs and activities.
Literature Review
By conducting a thorough literature review of previous studies and research pertaining to walkability, with a specific focus on measurement and assessment, it becomes apparent that there are noticeable deficiencies and erroneous approaches in the domestic research landscape. These shortcomings are particularly evident when it comes to result validation. While international research has diligently addressed methodological challenges, there is a dearth of investigation into the validation of these methods using questionnaire data in distinct localities. The necessity of undertaking this research lies in the imperative to introduce effective models for evaluating the state of local walkability. Additionally, it is crucial to validate the outcomes generated by these models and establish comparative analyses to discern their respective strengths and weaknesses. This rigorous examination is integral to unearthing the merits and limitations of each model, thus contributing to the advancement of knowledge in the field.
Methodology
This study adopts an applied research approach with a combined framework that incorporates both survey-based statistical analysis and descriptive-analytical data analysis methods. The research procedure, data collection, and analysis can be classified into two categories: quantitative and qualitative. Quantitative measures, assessment tools, and statistical techniques were employed to analyze the collected data, while a qualitative approach employing comparative techniques was utilized to compare two specific neighborhoods. Multiple methods were utilized to assess and comparatively analyze the walkability status of the studied neighborhoods. These methods include WalkScore, Smartraq, and space syntax models, each focusing on different dimensions of walkability. The analysis for WalkScore and Smartraq was performed using ArcGIS software, and a customized Python algorithm was developed and executed for the WalkScore method. For space syntax analysis, DepthMap software was employed. In the following section, statistical analysis was carried out to validate the outcomes derived from these models. This serves two purposes: enhancing the credibility of the models and confirming the reliability of the results in practical applications. This research falls under the comparative research category. The statistical population comprised residents residing in the Takhti and Marzdaran neighborhoods, with a randomly selected sample of 250 individuals.
Results
Based on the analysis conducted using the space syntax method, the findings reveal that the Takhti neighborhood exhibits a higher level of walkability quality compared to the Marzdaran neighborhood. This conclusion is supported by the evaluation of two critical indicators related to walkability in space syntax: connectivity and integration.
Table 1
Indicator
Neighborhood
Max
Min
Average
Integration
Takhti
3.21
0.84
1.75
Marzdaran
3.48
0.87
1.69
Connectivity
Takhti
30
1
3.5
Marzdaran
21
1
4.5
Intensity
Takhti
1.2
0.32
0.69
Marzdaran
1.25
0.42
0.79
Mean Depth
Takhti
7.82
2.79
4.47
Marzdaran
6.31
2.33
3.9n
The findings derived from the WalkScore method indicate that the residential blocks located within the Takhti neighborhood consistently exhibit significantly higher average scores in comparison to those situated within the Marzdaran neighborhood. These scores were formulated based on the proximity of each residential block to local amenities, encapsulating an essential aspect of neighborhood livability.
Table2
Neighborhood
Total Units
St.diversion
Interval Walkscore
Point
Average
Walkscore
point
Min
Max
Takhti
3070
0.16
85.87
98.92
93.07
Marzdaran
2742
0.73
43.75
97.91
77.86
The application of a method known as Smartraq brought to light notable disparities between the Takhti and Marzdaran neighborhoods in terms of intersection density, residential block density, and land use mix index. The findings indicate that the Takhti neighborhood exhibits a substantially higher magnitude in these metrics in comparison to its counterpart, the Marzdaran neighborhood.
Table 3
Neighborhood
Area
(m2)
intersections
Nodes
intersection index (per m2)
households
Residential Units Area (m2)
Residential density
Commercial land use area (m2)
Office land use area(m2)
Residential land use area (m2)
land use mix indices
Takhti
665946
419
307
6.29
7008
471821
0.018
140553
45604
371821
0.348
Marzdaran
1609772
311
293
1.93
10948
937252
0.011
62697
40771
937252
0.223
This research endeavors to employ rigorous statistical analyses in order to systematically investigate and substantiate the walkability attributes of the two focal neighborhoods, while simultaneously corroborating the results obtained from three distinct walkability models. Notably, regression analysis has effectively demonstrated that the aforementioned components decisively account for approximately 75% of the walkability variance discernible within the Takhti and Marzdaran neighborhoods.
The outcomes derived from regression analyses and the comparison of mean values derived from the perceptions of neighborhood residents pertaining to walkability indices convincingly illustrate that the Takhti neighborhood, boasting an average score of 3.52, exhibits a considerably higher level of walkability in comparison to the Marzdaran neighborhood, whose average rating stands at a modest 2.40.
Table 4
Indicates
Neighborhood
Statistics
n
Mean
Median
Mode
s.d
Var
Functional
Takhti
125
3.8
3.75
3.5
0.54
0.29
Marzdaran
125
2.20
2.32
2.3
0.43
0.48
Physical
Takhti
125
3.71
3.5
3.61
0.52
0.27
Marzdaran
125
2.53
2.12
2.75
0.62
0.39
Social
Takhti
125
4.12
4
4
0.54
0.32
Marzdaran
125
2.64
2.37
2.25
0.68
0.46
Environment
Takhti
125
2.46
2.25
2.25
0.83
0.69
Marzdaran
125
2.24
2.3
2.5
0.68
0.38
Total
Takhti
125
3.52
3.15
3.26
0.91
0.99
Marzdaran
125
2.40
2.90
2.75
0.663
0.441
Conclusion
In conclusion, the synthesis of findings arising from the WalkScore, Smartraq, and Spaces syntax methods has yielded valuable insights into the strengths and limitations of each approach within the assessment framework. Based on the comprehensive analysis, it can be deduced that all three models have demonstrated efficacy, with their outcomes exhibiting notable congruity. However, none of these methods in isolation can be deemed adequate for a holistic evaluation of neighborhood walkability. Therefore, it is advisable to combine these methodologies to achieve a more comprehensive assessment of pedestrian environments.
Unanimously, all three models concur on the walkability of the Takhti neighborhood, renowned for its historical character, intricate urban fabric, diverse land uses, and abundant amenities. Notably, this neighborhood excels across various indicators of walkability, encompassing ease of access to facilities, a mix of land uses, safety measures, population density, residential density, intersection density, continuity of networks, and street connectivity. As corroborated by the models, Takhti emerges as a notably pedestrian-friendly environment, diligently addressing the diverse needs of pedestrians, in stark contrast to the recently developed Marzdaran neighborhood.
Acknowledgments
The authors express their sincere gratitude to all individuals who have played a role in the conception and execution of this scholarly article.
