Walkability has become an important theme of urban design research and practice. Evidence suggests that environmental attractiveness can have a significant impact on the amount of walking activities that take place, but relatively little research exists on which environmental features linked to attractiveness increase walkability. Using a virtual reality experiment, the present study examined the effects on walkability of three key features, as defined by Jan Gehl, an influential urban planning practitioner and theorist: liveliness, high-quality façades and low buildings. A virtual reality simulation allowed isolating the effects of these features, while avoiding confounding factors, such as the presence of shops, which has been difficult to do in past field studies. Our study confirmed that the combination of features recommended by Gehl promoted walking activity in the study’s context. Further exploratory analyses suggested that improved façade quality was positively linked to walking activity, and that building height and liveliness had negligible effects. Our findings contribute to the existing understanding of walkability, which may benefit urban planning practice and models of walkability. Further research is necessary to confirm our results regarding the effects of specific features on walking activity in different contexts.

Singapore's urban planning and management is crossdomain in nature and need to be assessed using multi-domain indicators -such as SDGs. However, urban planning processes are often confronted with data interoperability issues. In this paper, we demonstrate how a Semantic Web Technology-based approach combined with a SWOT analysis framework can be used to develop an architecture for automated multi-domain evaluations of SDG-related planning targets. This paper describes an automated process of storing heterogeneous data in a semantic data store, deriving planning metrics and integrating a SWOT framework for the multi-domain evaluation of on-site solar energy potential across plots in Singapore. Our goal is to form the basis for a more comprehensive planning support tool that is based on a reciprocal relationship between innovations in SWT and a versatile SWOT framework. The presented approach has many potential applications beyond the presented energy potential evaluation.

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Urban planning relies on the definition, modelling and evaluation of multidimensional phenomena for informed decision-making. Urban building energy modelling, for instance, usually requires knowledge about the energy use profile and surface area of each use that takes place within a building. We do not have a detailed understanding of such information for mixed-use developments, which are gaining prominence in urban planning. In this paper, we developed a methodology to quantitatively define the characteristics of mixed-use developments using archetypes of programme profiles (ratios of each programme type) of a city’s mixed-use plots. We applied our methodology in Singapore, resulting in 163 mixed-use zoning archetypes using Singapore’s master plan data and Google Maps API data. In a case study, we demonstrated how these archetypes can be used to provide more detailed data for urban building energy modelling, including energy demand forecasts and energy supply system design. To enable future automation of the workflow, the archetype definitions were represented and stored as a machine-readable ontology. This ontology can later be extended with for example, the mobility properties of archetypes; thus, enabling the archetypes' use in other urban planning applications beyond building energy modelling.

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