Spatial interaction modelling (SIM) from social physics has been developed from Tobler’s ‘law’ that ‘near things are more related than distant things’. One of the key results from SIM is a gravity inequality between spatial and temporal interaction. Tobler’s law can be deconstructed into two further ‘laws’ relevant to the digital economy, namely, that ‘all things can be, but not necessarily will be, connected globally’; and secondly, ‘distance always matters, but time matters more’. A new developing SIM in this context comes from string theory where closed strings of relative time are converged by technology towards singularities in computers in a network. It is argued that the failure to understand this time-space compression from SIM was a major contributor to the electronic failure of the 2016 Australian Census and its shutdown, much to the embarrassment of the Australian government. It is argued that SIM should therefore be a consideration in any cybersecurity public policy formulation.

Urban planners routinely adhere to “park minimum standards” to ensure that the microclimatic, economic, and social benefits associated with public greenspace are socially equitable. While park standards specifying the size and placement of greenspace are common, specifications regarding the form, function, and human capacity of greenspace are less common. As such, the social equity of these latter greenspace characteristics is often unregulated, and likewise unobserved. To address this problem, I develop a novel method for classifying 4,265 preexisting greenspaces according to twelve functional characteristics, and then examine the social equity of these four identified greenspace types according to 4,524 Australian neighborhoods using three conceptually distinct operationalizations of social equity. These are: (1) accessibility operationalizing the travel cost of visiting greenspace; (2) provision operationalizing the local abundance of greenspace; and (3) population pressure operationalizing the local residential demands on greenspace and greenspace amenities. My research findings reveal multiple greenspace social inequities within my Brisbane Statistical Division study frame, and my methodology is portable for researchers, planners, and policy makers seeking a more nuanced understanding of how social inequities may exist within their cities.

For some time now, planners have relied on conventional methods of urban density measurements (e.g. Gross Density, Net Density, and Land Use per Capita) when engaged in strategic planning of our cities, especially when the issues of compactness, Transit Oriented Development (TOD) and smart city initiatives are the focus of discussion. Policy makers in the same way use density as an indicator to express quality of urban life. However, the interrelation of population, open spaces, and building densities in different urban morphologies is often overlooked. This argument emanates from the notion that approaches for density computations are based on limited consideration for the inclusion of significant parameters. This presentation focuses on the comparison of the inner- middle- and outer-suburbs of Metropolitan Melbourne using multi-measure densities approach. It leverages on existing initiatives such as AURIN, open data by local authorities and the adoption of a recently developed Urban Analytics Infrastructure, by consortium of six universities across Australia. With this, the harmonisation and standardisation of data and integration of multi-domain analytics was made possible. The application of the urban density tool in high building density urban setting like city of Melbourne indicates that access to open spaces are at a desirable level contrary to some previous assumptions, while revealing that, in a low building density and relatively low population density suburban area, access to open spaces remains problematic.