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Sustainability Rating Systems are standard methods for achieving sustainable development of buildings and urban landscapes. However, they suffer from low adoption and implementation rates, mainly due to labour-intensive evaluation processes. This study explores how recent advancements in big data, combined with the availability of new urban environment datasets, could advance sustainability rating systems in landscape development. We compared between existing computational technology (supply) and industry performance evaluation needs (demand) using a systematic review and survey of Israel’s professional communities as a case study. Of the existing indicators, Israeli professionals prioritised measuring socio-ecological indicators of landscapes in development projects, mainly at the urban level. Our review revealed that this level also holds available big data sustainability evaluation methods and technologies. Specifically, directed data for measuring ecology and volunteered and automated data for measuring social indicators. Such supply-demand links could significantly advance evaluation methods towards achieving a broader application of sustainable urban development.

Towards sustainability evaluation of urban landscapes using big data: a case study of Israel’s architecture, engineering and construction industry