We shape our buildings, but do they then shape us? A longitudinal analysis of pedestrian flows and development activity in Melbourne

Abstract

Cities are increasingly promoting walkability to tackle climate change, improve urban quality of life, and address socioeconomic inequities that auto-oriented development tends to exacerbate, prompting a need for predictive pedestrian flow models. This paper implements a novel network-based pedestrian flow model at a property-level resolution in the City of Melbourne. Data on Melbourne’s urban form, land-uses, amenities, and pedestrian walkways as well as weather conditions are used to predict pedestrian flows between different land-use pairs, which are subsequently calibrated against hourly observed pedestrian counts from automated sensors. Calibration allows the model extrapolate pedestrian flows on all streets throughout the city center based on reliable baseline observations, and to forecast how new development projects will change existing pedestrian flows. Longitudinal data availability also allows us to validate how accurate such predictions are by comparing model results to actual pedestrian counts observed in following years. Updating the built-environment data annually, we (1) test the accuracy of different calibration techniques for predicting foot-traffic on the city’s streets in subsequent years; (2) assess how changes in the built environment affect changes in foot-traffic; (3) analyze which pedestrian origin-destination flows explain observed foot-traffic during three peak weekday periods; and (4) assess the stability of model predictions over time. We find that annual changes in the built environment have a significant and measurable impact on the spatial distribution of Melbourne’s pedestrian flows. We hope this novel framework can be used by planners to implement “pedestrian impact assessments” for newly planned developments, which can complement traditional vehicular “traffic impact assessments”.

Walkability Compass—A Space Syntax Solution for Comparative Studies

“…We hypothesise that statistically significant correlations between analysed indices reveal spatial patterns of city walkability, and their synergy, like a compass, points to the strengths and weaknesses. Notably, the research method shifts from the street network analysis (we use it at the model validation stage) and follows mathematical graph centrality calculations proposed by [43,44]. The approach involves building footprint geometry for space syntax calculation, specifically the Reach (Re) and the Straightness (St) indices, herein used as walkability visual quality explanatory indicators.…”

impacto da pandemia de Covid-19 na qualidade de vida urbana:

“…As ideias de vitalidade urbana (urban vibrancy) [24] e caminhabilidade [25,26] ou cidades caminháveis (walkable cities; 15 minutes city) aparecem na literatura relacionando as características do ambiente construído com o comportamento dos habitantes. Os estudos demonstram as relações entre as diferentes atividades de uso do solo, fluxos de pedestres e uso de transporte veicular e como essas relações podem influenciar na qualidade de vida da população, melhorando a percepção subjetiva que os habitantes têm da cidade.…”

Modeling Barcelona sidewalks: A high resolution urban scale assessment of the geometric attributes of the walkable network

“…However, it should be noted that, apart from some specific works directed by A. Sevtsuk [ 17 ], the mapping and modeling unit of the previous research is the axial line of the street and not the exact description of the sidewalks as independent platforms interconnected by crosswalks. Although this simplification is sometimes argued by the inexistence of available cartographies of the sidewalks, this limitation should be considered when talking about walkability, as it necessarily implies a higher resolution in the cartography and detail in their interpretation.…”