This study investigates the potential of utilizing national building register data for identifying external wall types for detached houses constructed between 1941 and 1990. As Building Renovation Passports (BRPs) are envisioned to become key instruments in achieving EU-wide energy performance goals, the need for scalable, data-based, digital pre-audit tools becomes evident. By constructing a catalogue of 68 historically prevalent wall types and analyzing over 85,000 entries in the Estonian Building Register, the study quantifies the data’s applicability for estimating wall types through a process of elimination, utilizing an elimination ratio as a performance indicator of preciseness. Findings indicate that while 21% of houses contain ambiguous or unusable external wall data, over 65% exhibit external wall data where at least 73% of all potential wall types may be assumed unlikely. A perfect EBR-based identification, where all but one wall type is excluded, is possible as well, however these data types appear rarely in practice. This study provides validation for developing digital tools that generate preliminary BRPs and guide owners of detached houses in the early phases of renovation planning based on national register data.

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Precision of Identifying Exterior Wall Properties Based on National Building Register Data

  • Alois Andreas Põdra,
  • Ergo Pikas,
  • Targo Kalamees

摘要

This study investigates the potential of utilizing national building register data for identifying external wall types for detached houses constructed between 1941 and 1990. As Building Renovation Passports (BRPs) are envisioned to become key instruments in achieving EU-wide energy performance goals, the need for scalable, data-based, digital pre-audit tools becomes evident. By constructing a catalogue of 68 historically prevalent wall types and analyzing over 85,000 entries in the Estonian Building Register, the study quantifies the data’s applicability for estimating wall types through a process of elimination, utilizing an elimination ratio as a performance indicator of preciseness. Findings indicate that while 21% of houses contain ambiguous or unusable external wall data, over 65% exhibit external wall data where at least 73% of all potential wall types may be assumed unlikely. A perfect EBR-based identification, where all but one wall type is excluded, is possible as well, however these data types appear rarely in practice. This study provides validation for developing digital tools that generate preliminary BRPs and guide owners of detached houses in the early phases of renovation planning based on national register data.