The Open Data Potential for the Geospatial Characterisation of Building Stock on an Urban Scale: Methodology and Implementation in a Case Study

Energy renovation in buildings is one of the major challenges for the decarbonisation of the building stock. To effectively prioritise decision making regarding the adoption of the most efficient solutions and strategies, it is imperative to develop agile methods to determine the energy performance...

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Autores: Villanueva Díaz, Cristina, Álvarez Sanz, Milagros, Campos Celador, Álvaro, Terés Zubiaga, Jon
Tipo de recurso: artículo
Fecha de publicación:2024
País:España
Institución:Universidad del País Vasco
Repositorio:Addi. Archivo Digital para la Docencia y la Investigación
OAI Identifier:oai:addi.ehu.eus:10810/64488
Acceso en línea:http://hdl.handle.net/10810/64488
Access Level:acceso abierto
Palabra clave:geographic information system (GIS)
cadastral data
U-values
energy simulation
energy performance certificates (EPCs)
building archetypes
building features
UBEM data preparation
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spelling The Open Data Potential for the Geospatial Characterisation of Building Stock on an Urban Scale: Methodology and Implementation in a Case StudyVillanueva Díaz, CristinaÁlvarez Sanz, MilagrosCampos Celador, ÁlvaroTerés Zubiaga, Jongeographic information system (GIS)cadastral dataU-valuesenergy simulationenergy performance certificates (EPCs)building archetypesbuilding featuresUBEM data preparationEnergy renovation in buildings is one of the major challenges for the decarbonisation of the building stock. To effectively prioritise decision making regarding the adoption of the most efficient solutions and strategies, it is imperative to develop agile methods to determine the energy performance of buildings on an urban scale, in order to evaluate the impact of these improvements. In this regard, the data collection for feeding building energy models plays a key role in the accuracy and reliability of this issue, and the significant increase in recent years of available data from open data sources offers great potential in this respect. Thus, this study focuses on proposing a systematised and automated method for obtaining information from open data sources so as to obtain the most relevant geometric and thermal characteristics of residential buildings on an urban scale. The criteria for selecting the parameters to be obtained are based on their potential use as input data in different energy demand models aimed at assessing the energy performance of the building stock in a given area and, eventually, to evaluate the potential for improvement and the mitigation of different strategies. Geometric characterisation relies on obtaining and processing open data from cadastres to extract envelope surfaces categorised by orientation through QGIS (Free and Open Source Geographic Information System). For thermal characterisation, an automated process assigns different parameter-based information obtained from cadastral data, such as the year of construction. Finally, the applicability of the method is demonstrated through its implementation in the case study of Bilbao (Spain). The obtained results show that, although additional data should be collected when a detailed analysis of a building or building cluster has to be carried out, the existing open data can provide a first approximation, providing a first global view of the building stock in a region. It demonstrates the usability of the proposed method as an effective way to obtain and process these relevant data.The work presented in this paper was carried out within the EnePoMAP Project that was funded by “La Caixa” Foundation under the project code LCF/PR/SR20/52550013. The recruitment of the Author Cristina Villanueva-Díaz was funded by the European Union-Next Generation EU. The author Milagros Álvarez-Sanz is benefiting from the financial support of the University of the Basque Country (UPV-EHU), through the Vice-Rectorate of Research’s Personnel Research Training Program (2020). The publication fees of the paper were funded by the organisation of the 14th edition of the International Conference on Energy Efficiency and Sustainability in Architecture and Urbanism (EESAP 14), through a prize awarded to the material of this publication in recognition of the best communication submitted to the congress.MDPI2024202420242024info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10810/64488reponame:Addi. Archivo Digital para la Docencia y la Investigacióninstname:Universidad del País VascoIngléshttps://www.mdpi.com/2071-1050/16/2/652info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/es/© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/ 4.0/).oai:addi.ehu.eus:10810/644882026-06-18T09:23:17Z
dc.title.none.fl_str_mv The Open Data Potential for the Geospatial Characterisation of Building Stock on an Urban Scale: Methodology and Implementation in a Case Study
title The Open Data Potential for the Geospatial Characterisation of Building Stock on an Urban Scale: Methodology and Implementation in a Case Study
spellingShingle The Open Data Potential for the Geospatial Characterisation of Building Stock on an Urban Scale: Methodology and Implementation in a Case Study
Villanueva Díaz, Cristina
geographic information system (GIS)
cadastral data
U-values
energy simulation
energy performance certificates (EPCs)
building archetypes
building features
UBEM data preparation
title_short The Open Data Potential for the Geospatial Characterisation of Building Stock on an Urban Scale: Methodology and Implementation in a Case Study
title_full The Open Data Potential for the Geospatial Characterisation of Building Stock on an Urban Scale: Methodology and Implementation in a Case Study
title_fullStr The Open Data Potential for the Geospatial Characterisation of Building Stock on an Urban Scale: Methodology and Implementation in a Case Study
title_full_unstemmed The Open Data Potential for the Geospatial Characterisation of Building Stock on an Urban Scale: Methodology and Implementation in a Case Study
title_sort The Open Data Potential for the Geospatial Characterisation of Building Stock on an Urban Scale: Methodology and Implementation in a Case Study
dc.creator.none.fl_str_mv Villanueva Díaz, Cristina
Álvarez Sanz, Milagros
Campos Celador, Álvaro
Terés Zubiaga, Jon
author Villanueva Díaz, Cristina
author_facet Villanueva Díaz, Cristina
Álvarez Sanz, Milagros
Campos Celador, Álvaro
Terés Zubiaga, Jon
author_role author
author2 Álvarez Sanz, Milagros
Campos Celador, Álvaro
Terés Zubiaga, Jon
author2_role author
author
author
dc.subject.none.fl_str_mv geographic information system (GIS)
cadastral data
U-values
energy simulation
energy performance certificates (EPCs)
building archetypes
building features
UBEM data preparation
topic geographic information system (GIS)
cadastral data
U-values
energy simulation
energy performance certificates (EPCs)
building archetypes
building features
UBEM data preparation
description Energy renovation in buildings is one of the major challenges for the decarbonisation of the building stock. To effectively prioritise decision making regarding the adoption of the most efficient solutions and strategies, it is imperative to develop agile methods to determine the energy performance of buildings on an urban scale, in order to evaluate the impact of these improvements. In this regard, the data collection for feeding building energy models plays a key role in the accuracy and reliability of this issue, and the significant increase in recent years of available data from open data sources offers great potential in this respect. Thus, this study focuses on proposing a systematised and automated method for obtaining information from open data sources so as to obtain the most relevant geometric and thermal characteristics of residential buildings on an urban scale. The criteria for selecting the parameters to be obtained are based on their potential use as input data in different energy demand models aimed at assessing the energy performance of the building stock in a given area and, eventually, to evaluate the potential for improvement and the mitigation of different strategies. Geometric characterisation relies on obtaining and processing open data from cadastres to extract envelope surfaces categorised by orientation through QGIS (Free and Open Source Geographic Information System). For thermal characterisation, an automated process assigns different parameter-based information obtained from cadastral data, such as the year of construction. Finally, the applicability of the method is demonstrated through its implementation in the case study of Bilbao (Spain). The obtained results show that, although additional data should be collected when a detailed analysis of a building or building cluster has to be carried out, the existing open data can provide a first approximation, providing a first global view of the building stock in a region. It demonstrates the usability of the proposed method as an effective way to obtain and process these relevant data.
publishDate 2024
dc.date.none.fl_str_mv 2024
2024
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10810/64488
url http://hdl.handle.net/10810/64488
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://www.mdpi.com/2071-1050/16/2/652
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/es/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/es/
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Addi. Archivo Digital para la Docencia y la Investigación
instname:Universidad del País Vasco
instname_str Universidad del País Vasco
reponame_str Addi. Archivo Digital para la Docencia y la Investigación
collection Addi. Archivo Digital para la Docencia y la Investigación
repository.name.fl_str_mv
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