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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.…
Dokumentart: | Artikel (Wissenschaftlicher) |
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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): | Creative Commons 4.0 - Namensnennung (CC BY 4.0) |