Leveraging machine learning to generate a unified and complete building height dataset for Germany-Reference-Cited by-同舟云学术

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Leveraging machine learning to generate a unified and complete building height dataset for Germany

Published:2024-09 Issue: Volume:17 Page:100408
ISSN:2666-5468
Container-title:Energy and AI
language:en
Short-container-title:Energy and AI

Author:

Dabrock Kristina^ORCID,Pflugradt Noah,Weinand Jann Michael,Stolten Detlef

Funder

Helmholtz Association of German Research Centres

Publisher

Elsevier BV

Reference51 articles.

1. In focus: Energy efficiency in buildings,2022

2. Tabula building typologies in 20 European countries-making energy-related features of residential building stocks comparable;Loga;Energy Build,2016

3. Classification of building types in Germany: a data-driven modeling approach;Bandam;Data (Basel),2022

4. “EU Building Stock Observatory - Database - Energy Consumption.” Accessed: Nov. 21, 2023. [Online]. Available: https://building-stock-observatory.energy.ec.europa.eu/database/.

5. Eubucco v0.1: European building stock characteristics in a common and open database for 200+ million individual buildings;Milojevic-Dupont;Sci Data,2023

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