Exploring an unknown: Representative sample survey on structure and energy-related quality of the non-residential building stock in Germany
Publikation: Beitrag in Fachzeitschrift › Forschungsartikel › Beigetragen › Begutachtung
Beitragende
Abstract
The non-residential building stock in Germany, as in many other countries, is not fully represented in any official statistics, in contrast to residential buildings. This is surprising given the economic significance of this asset and its importance as a source of greenhouse gases. The knowledge gap was closed in a representative sample survey providing statistically valid data on structural parameters and energy-related characteristics of the non-residential building stock in Germany. This became possible because by December 2014 authoritative building polygons from all German cadastres were available in a national database for the first time. These geospatial data, adjusted for topological inconsistencies and supplemented with owner information in an on-site screening, were used as a sampling frame in the previously unknown population of the non-residential buildings, a new approach in building stock statistics worldwide. While the geometry of all buildings can be derived from the geospatial data, energy-related characteristics and renovation activities have to be obtained by interviews with the owners of the relevant non-residential buildings in the sample. With this methodology, regular monitoring of building stocks at reasonable costs becomes possible. It also can be transferred to other states with similar geospatial data infrastructure, in particular to other EU Member States.
Details
Originalsprache | Englisch |
---|---|
Aufsatznummer | 111407 |
Fachzeitschrift | Building and environment |
Jahrgang | 255 |
Publikationsstatus | Veröffentlicht - 1 Mai 2024 |
Peer-Review-Status | Ja |
Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- 3D building model, Building energy performance, Building stock, Building typology, Cadastral data, Energy renovation rate, Geospatial data, Horvitz-Thompson estimator, Non-residential building, Representative sample survey