Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/82176
Title: Computational modeling of land surface temperature using remote sensing data to investigate the spatial arrangement of buildings and energy consumption relationship
Authors: Faroughi, M
Karimimoshaver, M
Aram, F
Solgi, E
Mosavi, A
Nabipour, N
Chau, KW 
Issue Date: 2020
Source: Engineering applications of computational fluid mechanics, 2020, v. 14, no. 1, p. 254-270
Abstract: 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 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.
Keywords: Land surface temperature
Energy consumption
Residential buildings
Urban morphology
Urban sustainability
Remote sensing
Publisher: Taylor & Francis
Journal: Engineering applications of computational fluid mechanics 
ISSN: 1994-2060
EISSN: 1997-003X
DOI: 10.1080/19942060.2019.1707711
Rights: © 2020 The Author(s).
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use,distribution, and reproduction in any medium, provided the original work is properly cited.
The following publication Maryam Faroughi, Mehrdad Karimimoshaver, Farshid Aram, Ebrahim Solgi,Amir Mosavi, Narjes Nabipour & Kwok-Wing Chau (2020) Computational modeling of land surfacetemperature using remote sensing data to investigate the spatial arrangement of buildings andenergy consumption relationship, Engineering Applications of Computational Fluid Mechanics, 14:1,254-270 is available at https://dx.doi.org/10.1080/19942060.2019.1707711
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