Digital Data Gaps in Climate-Resilient Urban Renewal: Insights from Vilnius

Achieving climate neutrality and enhancing urban resilience require data-driven approaches to support deep energy retrofits and adaptive renewal strategies. However, leveraging digital data in urban planning remains challenging due to data fragmentation, lack of interoperability, inconsistent standards, and real-time and behavioural data gaps. This paper addresses these challenges by developing a novel neighbourhood renewal framework and applying it to a case study in Vilnius, Lithuania. The study integrates diverse open data sources, including 3D geospatial models, climate projections, socio-economic maps, and building performance indicators, to assess the feasibility of supporting climate-neutral and resilient urban renewal. The results show that available data is sufficient for preliminary scenario modelling and fundamental KPI estimation, particularly for energy use and spatial vulnerability analysis. However, comprehensive KPI evaluation is constrained by the absence of detailed indoor climate data, occupant behaviour insights, and life-cycle carbon metrics. These findings highlight the need for improved data collection methods, such as real-time sensing and community engagement tools, and better standardization to enable consistent and integrated analysis.