Spatial Network Analysis: The Decision-Making Process

Abstract

Data-driven research methods of analyzing and generating urban space reflect professional developments in the field of architecture, using urban data analytics as a driving force for the decision-making process. Urban data analytic methods help us to see and understand the city via the flow of spatial data. How might we look to alternative influences to improve the built environment? This paper focuses on the topic of Urban Network Analysis; nurturing an effective decision-making process by making invisible urban patterns visible through geo-spatial data. The associated research project created a platform to participate in the active relationship of urban form and its organization within the natural and built environments. The investigation aimed to provide goals for the future direction of urban planning and design guidelines. The computational analysis tools employed here demonstrate how to utilize geospatial data to analyze street networks, to create case studies of pattern and formation, and to expand our knowledge of relevant issues – social, political, economic, environmental, and spatial.1Instead of being given a problem, the project team was proactively seeking the problem, based in this case on Geographic Information System (GIS data. Creating meaningful solution to these issues is the role of designers and the future of architecture. In our problem seeking, we examined issues of accessibility, walkability, and pedestrian and vehicular movement by using computational analytic methods.2 The research helped us to understand the city via the flow of spatial data and its analysis applications. Using these tools, we simulated the growth of the city and analyzed it by looking at urban patterns. Several fundamental questions arose: In what ways do elements of urban form begin to affect an urban network? Are there other urban phenomena that contribute to forming an urban network? In cities where growth rate is rapid, transportation systems pose a challenge. How does spatial structuring of the city influence it? Is the analysis valuable? If so, why and who could benefit from its application? How could those factors begin to affect the analysis interpreted by the network analysis?