TWIN2EXPAND team members participated in the 14th International Space Syntax Symposium, presenting 3 project papers during the parallel session on Evidence-Based Design, chaired by Tim Stonor from Space Syntax Limited:

1. Challenges and Barriers of Integrating Spatial Models and Tools for Social-Economic Performance Assessment in Data-Scarce Urban Environments. The case of Cyprus. By Ana Ricchiardi, Iason Giraud, Nadia Charalambous, Ilaria Geddes. Abstract: Evidence-based design and planning (EBDP) is a methodology that integrates empirical evidence into the decision-making processes of design and planning. EBDP intentionally relies on the most trustworthy research findings to guide design choices, with the aim of optimising results within the realm of the built environment. Spatial models, tools, and methods have been developed to create evidence for Social-Economic Performance Assessment in urban environments. The models have proven to be effective in producing reliable results in data-rich environments. However, challenges appear in contexts such as Cyprus, where data availability and quality are limited, this is also the case for areas with limited institutional capacity. Employing techniques such as Data Audits, Stakeholder Meetings, and Urban Models based on Space Syntax, the study explores challenges linked to data accessibility and retrieval, as well as potential institutional setbacks in data-scarce urban environments. Methodologically, the study provides suggestions for overcoming such challenges with the development of Light-Weight Models. The study also offers suggestions for the overcoming of challenges related to institutional capacity, these suggestions relate to partnerships and collaboration, training and capacity building, pilot projects, and long-term commitments. The potential application of EBDP through lightweight models is promising for cities dealing with data constraints, offering a pathway to more efficient and responsive planning and design processes. This analysis of the Cypriot context can serve as a reference for similar contexts worldwide. 
2. Evaluating the use of space syntax modelling to understand changes to patterns of pedestrian movement: a post implementation study of five UK-based projects. By Iacovos Loizou, Ed Parham, Kayvan Karimi. Abstract: Due to the time architecture and urban planning projects take to move from design to completion, a historic challenge for built environment practitioners has been to better understand the longer-term impacts of physical intervention on patterns of activity. A second, more specific challenge for the space syntax community has been to understand how successfully these impacts could be predicted by modelling. Our paper documents the post-implementation analysis of five UK-based projects completed between 2003 and 2017 (Bloomberg HQ, Nottingham Old Market Square, One New Change, St Giles, and Trafalgar Square). We study how interventions affected patterns of pedestrian movement, identify factors influencing these changes, and investigate how well the space syntax techniques of the time were able to forecast the impact of proposals. The paper includes a comparative analysis of pedestrian movement data, before and after their redevelopment, as well as comparison to available projections made at the time. A combination of quantitative and qualitative methodologies is applied, combining data collection and statistical analysis with visual mapping. The findings of the research illustrate how pedestrian movement is complex and affected by multiple factors, but that the redesign of the built environment can change the dynamics and volumes of pedestrian movement at a local scale. The extent of change differs from site to site, with data collected here showing that space syntax models can predict changes in the (re)distribution of pedestrian movement. Accurately predicting flow volumes in a context as far as ten years in the future, which may be very different to the time when the forecast is run, is difficult. The paper concludes that there are clear relations between the impact of changes to patterns of visibility and the distribution of movement, and that space syntax models are a valuable tool for designers to test these interactions.
3. Scaling-Up Space Syntax Framing Evidence-Based Planning & Design. By Sepehr Zhand, Gareth Simons, Kayvan Karimi. Abstract: In the late 1970s, Space Syntax emerged as a way of understanding the built environment as a set of relations between spatial arrangements and overarching social, economic, and political processes. This understanding arose at a time when traditional modes of thinking on architecture and cities had been supplanted by modernist ideologies and the limitations of reductionist models of buildings and cities were becoming evident. The discourse of space syntax showed that analytical approaches to design and planning could not only identify problematic instances of realized projects but could also be applied to assess prospective design and planning programmes. Despite technological advancements, the adoption of space syntax has largely remained confined to academia and specialized firms, limited by the complexity required to implement these theories and the financial overheads of integrating advanced analytical processes. This paper considers the emergence of Evidence-Based Design and Planning (EBDP) as a framework which potentially aids the adoption and scaling of analytical approaches – including Space Syntax – to the design and planning field more generally. We provide a brief overview of perspectives on EBDP, introduce examples of evidence in both procedural and scientific forms, and review the quickly evolving ecosystem of open data sources and computational toolsets that are increasingly available. Maturing EBDP analytic toolsets and design methodologies are increasingly capable of overcoming technical and financial hurdles which historically hindered adoption of analytical approaches, therefore enhancing the applicability and scalability of evidence informed analytical approaches in urban design and planning. However, whereas such methods are increasingly powerful, accessible, and generalisable, challenges to their adoption remain.

This event was a fantastic platform to receive valuable feedback from the generous and knowledgeable space syntax community. We had insightful discussions about data scarcity, modeling with limited data, and future perspectives that include AI. These conversations highlighted the importance of understanding who we are designing for and how we can improve our methods.

Full papers available from our publications section.