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

Abstract

Predicting how changes to the urban environment will affect town centre vitality, mediated as pedestrian flows, is important for environmental, social and economic sustainability. This study is a longitudinal investigation of before and after urban environmental change in a town centre and its association with vitality. The case study baseline is Cardiff town centre in 2007, prior and after major changes instigated by re-configuring Cardiff public and quasi-public street layout due to implementation of the St David's Phase 2 retail development.We present a Multivariate Hybrid Spatial Network Analysis (MHSpNA) model, which bridges the gap between existing Spatial Network Analysis models and four stage modelling techniques. Multiple theoretical flows are computed based on retail floor area (everywhere to shops, shop to shop, stations to shops and parking to shops). The calibration process determines a suitable balance of these to best match observed pedestrian flows, using generalized cross-validation to prevent overfit. Validation shows that the 2007 model successfully predicts vitality as pedestrian flows measured in 2010 and 2011. This is the first time, to our knowledge, that a vitality-pedestrian flow model has been evaluated for its ability to forecast town centre vitality changes over time.

Associating street-network centrality with spontaneous and planned subcentres

“…Street-network centrality should be accounted for before locating growth and consolidation plans. Specialised software for measuring network-based relationships in cities supplement generic GIS network platforms and include Space Syntax (Hillier, 1999), Urban Network Analysis (UNA) (Sevtsuk and Mekonnen, 2012) and sDNA (Cooper et al, 2019). Methodological developments from wider network science have found their way into urban studies, such as the early application of network-based centrality measures to urban design (Hillier and Hanson, 1984), network kernel density estimation (Han et al, 2019) and network evolution models (Masucci et al, 2014).…”

“…We constructed a set of parsimonious models that regress street network link-based cluster descriptors on link-based centrality using sDNA+, a plug-in for ArcGIS (Chiaradia et al, 2019; Cooper et al, 2019), with controls for housing density, other choice dimensions and land price. Measuring the clustering tendencies of different kinds of economic units in urban space has been a major challenge in assessing agglomeration patterns, scale and intensity of facilities, and there is a need to diversify the methodology to accurately measure spatial concentration or dispersion of economic units in an area (Garracho-Rangel et al, 2013; Law, 2017; Scoppa and Peponis, 2015).…”

Effects of green space on walking: Does size, shape and density matter?

“…We used the average betweenness in a park’s catchment to indicate the quality of street connectivity of neighbourhoods around a park. Betweenness centrality was measured using sDNA (Cooper et al, 2016).…”

A Systematic Measurement of Street Quality through Multi-Sourced Urban Data: A Human-Oriented Analysis

“…Cooper et al noted that for Angular-Euclidean hybrid metric, 0.25 ≤ a ≤ 0.5 gave good results [84]. It has been reported that a calibration of half angular–half Euclidean metric gives a stable result in terms of interpreting pedestrian movement [85].…”