Data Quality in Urban Digital Twins: Challenges in the Virtualization of Florence's Historic Heritage

Abstract

The increasing vulnerability of historic city centres to climate change and environmental risks demands the use of high-resolution digital tools for urban planning and heritage protection. In this context, the Digital City & River Twin (DiC&RT) framework is being tested in the historic centre of Florence to examine data quality and interoperability within Urban Digital Twins. The analysis focuses on the geometric and semantic representation of buildings, integrating MMS surveys and UAV photogrammetry. It addresses critical issues related to building density, visual occlusion, and data heterogeneity, proposing multi-technological solutions for more accurate modeling. The thematic component is geared toward multi-risk analysis, with particular emphasis on hydraulic and seismic scenarios, supported by controlled vocabularies and interoperable data structures such as CityGML. The case study highlights how data quality, consistency, and granularity are key requirements for the effective operation of urban Digital Twins in resilience management and heritage conservation.