Objective 5Ds-based measures in conjunction with syntactic properties of street network to assess walkability in residential neighborhoods in Putrajaya, Malaysia

Recently, neighbourhood walkability has emerged as a critical concept for sustainable urban development and promoting active mobility. The creation and replication of walkability indices involve the use of geographic information systems (GIS) and require exploration of assumptions implicit in various research disciplines. While the current GIS-based approach to neighbourhood walkability assessment relies on the 5Ds of the built environment (density, design, diversity, destination accessibility, and distance to transit), these metrics have been shown to lack contextual validity and be scaledependent. Combining them with syntactic metrics of street networks based on space syntax, has been proposed as a solution, holding greater potential to explain walking behaviour. However, despite this theoretical promise, the compatibility of these two measures is constrained at neighbourhood level due to the absence of an operational framework for combining the parameters of both methods, and the lack of geographical standards for data aggregation. Therefore, this study aims to develop a model for neighbourhood walkability assessment, based on 5Ds and street network metrics across different neighbourhood scales. Putrajaya city was chosen for this study due to its dendriform network structure conducive to space syntax analysis. Using GIS, multiple buffer-service areas (240, 400, 600, and 1,000 meters) were generated around each housing unit within Precincts 9 and 11 (N = 2,392). Data on the built environment and street network were sourced, respectively, from the Integrated Land Use Planning Information System (I-Plan) and OpenStreetMap (OSM). The study begins by examining the association and impact of syntactic metrics in shaping the 5Ds. Subsequently, it tests each method against the observed walking volume collected through systematic manual counting at 123 observation gates, followed by investigating the impact of scale selection on each method, and finally, it examines the predictability of the combined model across multiple scales. Utilizing correlation, linear, and negative binomial regression, this study revealed several key findings. Firstly, syntactic metrics emerged not just as street-related but also as functional measures, representing various aspects of the built environment influencing walking behaviour. Specifically, the distribution of distances and land use patterns within the neighbourhood. Secondly, the assumption of syntactic metrics demonstrated a superior explanatory power for pedestrian volume when compared to the 5Ds across diverse geographical scales. Thirdly, the findings underscore the substantial impact of scale selection on the association between GIS-based attributes and pedestrian counting. Nevertheless, syntactic metrics consistently outperform 5Ds, irrespective of the analysis scale chosen. Moreover, the results suggested that a 600-meter network scale appears most suitable for identifying the association between the combination of the 5Ds and pedestrian counts in residential neighbourhoods. Finally, syntactic metrics, when integrated with 5Ds measures, significantly enhance the overall predictability of the model at both micro and macro levels. Building on these outcomes, a novel syntacticbased index, SLM (Syntactic Local Measure) was introduced. SLM demonstrated high predictability of walking volume at the neighbourhood level, requiring less data and mitigating scaling impacts. This dissertation holds the potential to advance objective analytical methods, particularly relevant to Malaysia or similar context where shorter walking distances due to the tropical climate pose unique challenges for promoting active transportation.

Text 120711.pdf Download (1MB) Official URL or Download Paper: http://ethesis.upm.edu.my/id/eprint/18516

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