How to design the metro network for maximal accessibility potential? A comparative analysis of Shanghai

[EN] As metro systems become more extensive they also become more complex, an analysis of the network shape and structure can be of substantive help for planners at early design stages to effectively evaluate multiple alternatives. This study compares the design scenarios of adding a typical circular ring metro line versus a novel alternative using two overlapping ellipse metro line rings. Ring metro lines have been found to be an important factor in network topology and the improvement of metro system network efficiency and reliability. A ring metro line can improve the connectivity and directness of a metro system network and thus improve transit by reducing mean travel time. A highly concentrated and dense central core surrounded by remote residential neighbourhoods, a monocentric city, would make circumferential travel less effective than in larger polycentric city with several sub-regional centres. Using Shanghai metro system 2017 as baseline, we consider the novel morphological alternative scenario of two overlapping ellipses and compare its relative performance to the more traditional ring metro line, by using graph theoretical topological and Euclidean centrality measures, otherwise known as’ closeness’ or ‘accessibility’ or ‘all to all’ mean distance. The comparison between the two scenarios shows that the two overlapping ellipse scenario is better at minimizing mean Topological distance, Mean Euclidean distance is well-correlated to actual travel time, The two-ellipse scenario leads to a reduction of 8% of network mean topological distance, while a simple ring reduces it only by 0.13%.Zhang, L.; Chiaradia, A. (2018). How to design the metro network for maximal accessibility potential? A comparative analysis of Shanghai. En 24th ISUF International Conference. Book of Papers. Editorial Universitat Politècnica de València. 1223-1231. https://doi.org/10.4995/ISUF2017.2017.4975OCS1223123

sDNA: how and why we reinvented Spatial Network Analysis for health, economics and active modes of transport

We introduce sDNA, a GIS/CAD tool and methodology for analysis of spatial networks. The design decisions behind the tool are documented, in particular the choice of standardizing on the network link in order to match existing data standards and increase computational efficiency. We explore the effects of this decision on algorithm design, and present results that validate our decision to depart from a recent tradition and revive a much older one

Measuring the impact of spatial network layout on community social cohesion: A cross-sectional study

Background: There is now a substantial body of research suggesting that social cohesion, a collective characteristic measured by the levels of trust, reciprocity and formation of strong social bonds within communities, is an important factor in determining health. Of particular interest is the extent to which factors in the built environment facilitate, or impede, the development of social bonds. Severance is a characteristic of physical environments which is hypothesized to inhibit cohesion. In the current study we test a number of characteristics of spatial networks which could be hypothesized to relate either to severance, or directly to community cohesion. Particular focus is given to our most promising variable for further analysis (Convex Hull Maximum Radius 600 m).Methods: In the current study we analysed social cohesion as measured at Enumeration District level, aggregated from a survey of 10,892 individuals aged 18 to 74 years in the Caerphilly Health and Social Needs Cohort Study, 2001. In a data mining process we test 16 network variables on multiple scales. The variable showing the most promise is validated in a test on an independent data set. We then conduct a multivariate regression also including Townsend deprivation scores and urban/rural status as predictor variables for social cohesion.Results: We find convex hull maximum radius at a 600 m scale to have a small but highly significant correlation with social cohesion on both data sets. Deprivation has a stronger effect. Splitting the analysis by tertile of deprivation, we find that the effect of severance as measured by this variable is strongest in the most deprived areas. A range of spatial scales are tested, with the strongest effects being observed at scales that match typical walking distances.Conclusion: We conclude that physical connectivity as measured in this paper has a significant effect on social cohesion, and that our measure is unlikely to proxy either deprivation or the urban/rural status of communities. Possible mechanisms for the effect include intrinsic navigability of areas, and the existence of a focal route on which people can meet on foot. Further investigation may lead to much stronger predictive models of social cohesion. © 2014 Cooper et al.; licensee BioMed Central Ltd.Link_to_subscribed_fulltex

Using multiple hybrid spatial design network analysis to predict longitudinal effect of a major city centre redevelopment on pedestrian flows

Predicting how changes to the urban environment layout will affect the spatial distribution of pedestrian flows is important for environmental, social and economic sustainability. We present longitudinal evaluation of a model of the effect of urban environmental layout change in a city centre (Cardiff 2007–2010), on pedestrian flows. Our model can be classed as regression based direct demand using Multiple Hybrid Spatial Design Network Analysis (MH-sDNA) assignment, which bridges the gap between direct demand models, facility-based activity estimation and spatial network analysis (which can also be conceived as a pedestrian route assignment based direct demand model). Multiple theoretical flows are computed based on retail floor area: everywhere to shops, shop to shop, railway stations to shops and parking to shops. Route assignment, in contrast to the usual approach of shortest path only, is based on a hybrid of shortest path and least directional change (most direct) with a degree of randomization. The calibration process determines a suitable balance of theoretical flows to best match observed pedestrian flows, using generalized cross-validation to prevent overfit. Validation shows that the model successfully predicts the effect of layout change on flows of up to approx. 8000 pedestrians per hour based on counts spanning a 1 km2 city centre, calibrated on 2007 data and validated to 2010 and 2011. This is the first time, to our knowledge, that a pedestrian flow model with assignment has been evaluated for its ability to forecast the effect of urban layout changes over time