Varying data on urban trees complicates meeting user needs for digital twins of urban green infrastructure

Digital twins are becoming common in urban planning and space management. However, dynamic modelling urban green infrastructure is lagging behind this development. Using interviews, online polls and questionnaires, we identified user groups and needs for a digital model of urban green infrastructure for pilot cities in Estonia and Finland. We found that several user needs were associated with users being able to see and analyse the anticipated future development of existing and proposed vegetation. To meet these needs, digital twins require projection models that are calibrated using regionally suitable data. In our case study of urban tree growth, based on literature searches of pilot area species, the availability of suitable data was limited and varied per species. This suggests that initial projection models may need to be built on expert estimates. Suitable empirical data can later be retrieved by monitoring the focus areas of digital twins, but this requires time.