lnu.sePublications
System disruptions
We are currently experiencing disruptions on the search portals due to high traffic. We are working to resolve the issue, you may temporarily encounter an error message.
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Spatial interaction model of energy demand of buildings and satellite thermal imageries using Geographically Weighted Regression analysis
Linnaeus University, Faculty of Technology, Department of Built Environment and Energy Technology.ORCID iD: 0000-0001-9036-119x
Linnaeus University, Faculty of Technology, Department of Built Environment and Energy Technology.ORCID iD: 0000-0003-4405-1056
Linnaeus University, Faculty of Technology, Department of Built Environment and Energy Technology.ORCID iD: 0000-0003-0189-474x
2022 (English)In: eceee 2022 Summer Study on energy efficiency: agents of change, European Council for an Energy Efficient Economy (ECEEE), 2022, p. 559-569Conference paper, Published paper (Refereed)
Sustainable development
SDG 7: Ensure access to affordable, reliable, sustainable and modern energy for all
Abstract [en]

The Energy Performance Certificate (EPC) is an important information tool to improve the energy performance (EP) of buildings. However, establishing the EP of building is tedious, time-consuming, and numerous input parameters are required in its estimation. However, the usefulness of EPC for the implementation of customized solutions by the supply-side actors require that EPCs are available for all buildings, easily accessible, credible, and recent. However, this is not the case at present. This could be addressed by employing remote sensing dataset along with GIS based spatial analysis techniques. In the present study, the spatial regression analysis technique is implemented in identifying the spatial relation between the input variables and the EP of selected 4541 buildings within Växjö municipality, Sweden.

The input variables used in the study include the land surface temperature (LST) maps of summer and spring of 2020 derived through the thermal band of Landsat 8 satellite data, built-up and openland neighbourhood maps prepared from the land use/land cover map 2020 of the study region. Building topology including year of construction, type, category, and complexity of buildings are also used to identify the relation between the input variables and the EP of those selected buildings. Results of spatial regression analysis reveal a significant positive relation between the LST and EP of buildings (regression co-efficient are 0.86 and 0.95 in spring and summer respectively).

The stronger correlation in summer could be because of the availability of higher intensity of solar radiation which gets absorbed by the built-up regions. Results suggest that the LST maps derived from satellite imageries could provide information on the EP of buildings. This could be beneficial to local decision makers and policy regulators in identifying the buildings with lower EP with better accuracy with less dependence on EPC data which are sometimes not available or not updated. The results could also be beneficial to investment bankers, real estate companies during the purchase and sale of a building. Policy makers and renovation companies could get benefited with the results in preliminary identification of the potential hotspots for district energy renovation where the EP of buildings is poorer. This could help achieve the goal of sustainable urban planning targeting energy reduction, climate adaptation, through implementation of effective energy management strategies in the building sector.

Place, publisher, year, edition, pages
European Council for an Energy Efficient Economy (ECEEE), 2022. p. 559-569
Series
eceee Summer Study proceedings, ISSN 1653-7025, E-ISSN 2001-7960 ; 2022
National Category
Building Technologies Energy Systems
Research subject
Technology (byts ev till Engineering), Bioenergy Technology
Identifiers
URN: urn:nbn:se:lnu:diva-115044Scopus ID: 2-s2.0-85178577223ISBN: 9789198827002 (print)OAI: oai:DiVA.org:lnu-115044DiVA, id: diva2:1679196
Conference
A New Reality, eceee 2022 Summer Study on energy efficiency
Available from: 2022-06-30 Created: 2022-06-30 Last updated: 2024-06-05Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

ScopusPublisher's fulltextPresentation

Authority records

Devendran, Aarthi AishwaryaMahapatra, KrushnaMainali, Brijesh

Search in DiVA

By author/editor
Devendran, Aarthi AishwaryaMahapatra, KrushnaMainali, Brijesh
By organisation
Department of Built Environment and Energy Technology
Building TechnologiesEnergy Systems

Search outside of DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 129 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf