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Computational modeling of land surface temperature using remote sensing data to investigate the spatial arrangement of buildings and energy consumption relationship

  • The effect of urban form on energy consumption has been the subject of various studies around the world. Having examined the effect of buildings on energy consumption, these studies indicate that the physical form of a city has a notable impact on the amount of energy consumed in its spaces. The present study identified the variables that affected energy consumption in residential buildings andThe effect of urban form on energy consumption has been the subject of various studies around the world. Having examined the effect of buildings on energy consumption, these studies indicate that the physical form of a city has a notable impact on the amount of energy consumed in its spaces. The present study identified the variables that affected energy consumption in residential buildings and analyzed their effects on energy consumption in four neighborhoods in Tehran: Apadana, Bimeh, Ekbatan-phase I, and Ekbatan-phase II. After extracting the variables, their effects are estimated with statistical methods, and the results are compared with the land surface temperature (LST) remote sensing data derived from Landsat 8 satellite images taken in the winter of 2019. The results showed that physical variables, such as the size of buildings, population density, vegetation cover, texture concentration, and surface color, have the greatest impacts on energy usage. For the Apadana neighborhood, the factors with the most potent effect on energy consumption were found to be the size of buildings and the population density. However, for other neighborhoods, in addition to these two factors, a third factor was also recognized to have a significant effect on energy consumption. This third factor for the Bimeh, Ekbatan-I, and Ekbatan-II neighborhoods was the type of buildings, texture concentration, and orientation of buildings, respectively.zeige mehrzeige weniger

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Metadaten
Dokumentart:Artikel (Wissenschaftlicher)
Verfasserangaben: Maryam Faroughi, Mehrdad KarimimoshaverORCiD, Farshid AramORCiD, Ebrahim Solgi, Amir MosaviORCiD, Narjes NabipourORCiD, Kwok-Wing ChauORCiD
DOI (Zitierlink):https://doi.org/https://doi.org/10.1080/19942060.2019.1707711Zitierlink
URN (Zitierlink):https://nbn-resolving.org/urn:nbn:de:gbv:wim2-20200110-40585Zitierlink
URL:https://www.tandfonline.com/doi/full/10.1080/19942060.2019.1707711
Titel des übergeordneten Werkes (Englisch):Engineering Applications of Computational Fluid Mechanics
Verlag:Taylor & Francis
Sprache:Englisch
Datum der Veröffentlichung (online):05.01.2020
Datum der Erstveröffentlichung:05.01.2020
Datum der Freischaltung:10.01.2020
Veröffentlichende Institution:Bauhaus-Universität Weimar
Institute und Partnereinrichtugen:Fakultät Bauingenieurwesen / Institut für Strukturmechanik (ISM)
Jahrgang:2020
Ausgabe / Heft:Volume 14, No. 1
Seitenzahl:17
Erste Seite:254
Letzte Seite:270
Freies Schlagwort / Tag:urban morphology; urban sustainability
Land surface temperature; energy consumption; remote sensing; residential buildings; smart cities
GND-Schlagwort:Fernerkung; Intelligente Stadt; Oberflächentemperatur
DDC-Klassifikation:000 Informatik, Informationswissenschaft, allgemeine Werke
BKL-Klassifikation:06 Information und Dokumentation
Lizenz (Deutsch):License Logo Creative Commons 4.0 - Namensnennung (CC BY 4.0)