Mapping soft densification: a geospatial approach for identifying residential infill potentials

Abstract

Infill development policies have been widely adopted as strategies to reduce urban sprawl and to promote sustainable urban transformation. However, little empirical data are available to analyse infill processes and to facilitate building activity on infill potentials. This is especially true for small-scale residential infill, which often takes place on vacant or underused lots as soft densification. To address this issue, a geospatial method is presented that enables automatic detection of vacant lots for large areas. Cadastral data are used to analyse spatio-temporal development for the period 2011–21 in a German study area, containing large cites as well as rural municipalities. The results show that every fourth vacant lot was mobilised since 2011. However, additional vacant lots emerged in rural areas as new residential development areas are not fully built-up, resulting in a net increase of vacant lots. Although the quantity of vacant lot areas in 2021 suggests a high potential for residential infill, the main development on these infill sites is expected to promote additional single-family housing rather than more dense structures. Practice relevance Automatic identification and monitoring of infill potentials and development are important both for policymaking and for local planning practitioners. For small municipalities with little financial capacities, the approach can provide an overview of their vacant lots and can serve as a basis for strategic planning decisions. For the regional or national level, a yearly monitoring schedule can be established at little cost. Although the approach proves to be robust regarding its precision and is promising for a nationwide application, the data availability for the whole of Germany is awaited and the method needs to be optimised to implement the workflow in practice.

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