The purpose of this paper is to develop an approach to urban environment management through analysis of “urban emptiness” based on user-generated big data.

The research design is based on creating a theoretical model of urban emptiness as a multilayer phenomenon in the city space and then developing an applied approach to map its different types through user-generated and open big data from multiple online sources.

The paper provides a definition and a theoretical model of “urban emptiness” as a multilayer phenomenon integrated into the complexity of the city system and as a resource for sustainable urban development. The paper presents a methodological approach to analyse urban emptiness based on spontaneous user-generated geolocated open data emerging online. This approach is applied to the Russian city of St Petersburg with a demonstration of the data set formation based on multiple sources and an interpretation of the preliminary results.

The paper focuses on the under-researched phenomenon of urban emptiness, which leads to a certain speculation of propositions and lack of generalisability of the results. Therefore, the researchers are encouraged to further test the proposed propositions.

The paper describes urban emptiness as a resource in urban development and gives recommendations on how to account for it in sustainable urban environment management, in particular, in limiting urban sprawl.

This paper consolidates data-driven methods to create an integrated approach to urban environment management from an original standpoint – analysis of urban emptiness.