3,647
Views
24
CrossRef citations to date
0
Altmetric
Articles

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

, , ORCID Icon, , ORCID Icon, & show all
Pages 254-270 | Received 14 Oct 2019, Accepted 16 Dec 2019, Published online: 04 Jan 2020

References

  • Alhamwi, A., Medjroubi, W., Vogt, T., & Agert, C. (2017). GIS-based urban energy systems models and tools: Introducing a model for the optimisation of flexibilisation technologies in urban areas. Applied Energy, 191, 1–9. doi: 10.1016/j.apenergy.2017.01.048
  • Anderson, J. E., Wulfhorst, G., & Lang, W. (2015). Energy analysis of the built environment - A review and outlook. Renewable and Sustainable Energy Reviews, 44, 149–158. Elsevier Ltd. doi: 10.1016/j.rser.2014.12.027
  • Aram, F., Higueras García, E., Solgi, E., & Mansournia, S. (2019). Urban green space cooling effect in cities. Green Space Cooling Effect in Cities. Heliyon, 5, e01339. doi: 10.1016/j.heliyon.2019
  • Aram, F., Solgi, E., García, E. H., Mohammadzadeh, S. D., Mosavi, A., & Shamshirband, S. (2019). Design and validation of a computational program for analysing mental maps: Aram mental map analyzer. Sustainability (Switzerland), 11(14), doi: 10.3390/su11143790
  • Aram, F., Solgi, E., Higueras García, E., Mosavi, A., & Várkonyi-Kóczy, A. R. (2019). The cooling effect of large-scale urban parks on surrounding area thermal comfort. Energies, 12(20), 3904. doi: 10.3390/en12203904
  • Aram, F., Solgi, E., & Holden, G. (2019). The role of green spaces in increasing social interactions in neighborhoods with periodic markets. Habitat International, 84, 24–32. doi: 10.1016/j.habitatint.2018.12.004
  • Ayanlade, A. (2017). Variations in urban surface temperature: An assessment of land use change impacts over Lagos metropolis. Weather, 72(10), 315–319. doi: 10.1002/wea.2925
  • Baker, N., & Steemers, K. (2000). Energy and environment in architecture; A tehcnical design guide. Taylor.&.Francis. Taylor & Francis Group. doi: 10.1017/CBO9781107415324.004
  • Baker, R. (2018). Heat reduction capabilities of urban tree species. Geographical Bulletin - Gamma Theta Upsilon, 59(2), 75–86.
  • Barile, G., Leoni, A., Pantoli, L., & Stornelli, V. (2018). Real-time autonomous system for structural and environmental monitoring of dynamic events. Electronics (Switzerland), 7(12), doi: 10.3390/electronics7120420
  • Bitelli, G., Conte, P., Csoknyai, T., Franci, F., Girelli, V. A., & Mandanici, E. (2015). Aerial thermography for energetic modelling of cities. Remote Sensing, 7(2), 2152–2170. doi: 10.3390/rs70202152
  • Bokaie, M., Zarkesh, M. K., Arasteh, P. D., & Hosseini, A. (2016). Assessment of urban heat island based on the relationship between land surface temperature and land use/ land cover in Tehran. Sustainable Cities and Society, 23, 94–104. doi: 10.1016/j.scs.2016.03.009
  • Chen, S., Hu, D., Wong, M. S., Ren, H., Cao, S., Yu, C., & Ho, H. C. (2019). Characterizing spatiotemporal dynamics of anthropogenic heat fluxes: A 20-year case study in Beijing–Tianjin–Hebei region in China. Environmental Pollution, 249, 923–931. doi: 10.1016/j.envpol.2019.03.113
  • Chun, B., & Guldmann, J. M. (2018). Impact of greening on the urban heat island: Seasonal variations and mitigation strategies. Computers, Environment and Urban Systems, 71, 165–176. doi: 10.1016/j.compenvurbsys.2018.05.006
  • Crawford, B., Grimmond, S. B., Gabey, A., Marconcini, M., Ward, H. C., & Kent, C. W. (2018). Variability of urban surface temperatures and implications for aerodynamic energy exchange in unstable conditions. Quarterly Journal of the Royal Meteorological Society, 144(715), 1719–1741. doi: 10.1002/qj.3325
  • de Lemos Martins, T. A., Faraut, S., & Adolphe, L. (2019). Influence of context-sensitive urban and architectural design factors on the energy demand of buildings in Toulouse, France. Energy and Buildings, 190, 262–278. doi: 10.1016/j.enbuild.2019.02.019
  • Deo, R. C., & Şahin, M. (2017). Forecasting long-term global solar radiation with an ANN algorithm coupled with satellite-derived (MODIS) land surface temperature (LST) for regional locations in Queensland. Renewable and Sustainable Energy Reviews, 72, 828–848. Elsevier Ltd. doi: 10.1016/j.rser.2017.01.114
  • Dwivedi, A. (2019). Macro- and micro-level studies using Urban Heat Islands to simulate effects of greening, building materials and other mitigating factors in Mumbai city. Architectural Science Review, 62(2), 126–144. doi: 10.1080/00038628.2019.1578193
  • Dwivedi, A., Khire, M. V., Mohan, B. K., & Shah, S. (2019). The role of structure cooling to reduce the effect of urban heat island in Mumbai. Advances in Building Energy Research, 13, 174–192. doi: 10.1080/17512549.2018.1488611
  • Dyce, D. R., & Voogt, J. A. (2018). The influence of tree crowns on urban thermal effective anisotropy. Urban Climate, 23, 91–113. doi: 10.1016/j.uclim.2017.02.006
  • Echarri, V., Espinosa, A., & Rizo, C. (2017). Thermal transmission through existing building enclosures: Destructive monitoring in intermediate layers versus non-destructive monitoring with sensors on surfaces. Sensors (Switzerland), 17(12), doi: 10.3390/s17122848
  • Esau, I., Miles, V., Varentsov, M., Konstantinov, P., & Melnikov, V. (2019). Spatial structure and temporal variability of a surface urban heat island in cold continental climate. Theoretical and Applied Climatology, 137, 2513–2528. doi: 10.1007/s00704-018-02754-z
  • Ewing, R., & Rong, F. (2008). The impact of urban form on U.S. residential energy use. Housing Policy Debate, 19(1), 1–30. doi: 10.1080/10511482.2008.9521624
  • Feigenwinter, C., Vogt, R., Parlow, E., Lindberg, F., Marconcini, M., Del Frate, F., & Chrysoulakis, N. (2018). Spatial Distribution of Sensible and Latent Heat Flux in the City of Basel (Switzerland). IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(8), 2717–2723. doi: 10.1109/JSTARS.2018.2807815
  • Fox, J., Osmond, P., & Peters, A. (2018). The effect of building facades on outdoor microclimate-Reflectance recovery from terrestrial multispectral images using a robust empirical line method. Climate, 6(3), doi: 10.3390/cli6030056
  • Garcia-Santos, V., Cuxart, J., Jimenez, M. A., Martinez-Villagrasa, D., Simo, G., Picos, R., & Caselles, V. (2019). Study of temperature heterogeneities at Sub-Kilometric scales and influence on surface-atmosphere energy interactions. IEEE Transactions on Geoscience and Remote Sensing, 57(2), 640–654. doi: 10.1109/TGRS.2018.2859182
  • Hu, L., & Wendel, J. (2019). Analysis of urban surface morphologic effects on diurnal thermal directional anisotropy. ISPRS Journal of Photogrammetry and Remote Sensing, 148, 1–12. doi: 10.1016/j.isprsjprs.2018.12.004
  • Javanroodi, K., Nik, V. M., & Mahdavinejad, M. (2019). A novel design-based optimization framework for enhancing the energy efficiency of high-rise office buildings in urban areas. Sustainable Cities and Society, 49, doi: 10.1016/j.scs.2019.101597
  • Jiang, Y., & Weng, Q. (2017). Estimation of hourly and daily evapotranspiration and soil moisture using downscaled LST over various urban surfaces. GIScience and Remote Sensing, 54(1), 95–117. doi: 10.1080/15481603.2016.1258971
  • Kamal-chaoui, L., & Robert, A. (2009). Competitive cities and climate change. Development, 172 (October). Retrieved from http://www.forum15.org.il/art_images/files/103/COMPETITIVE-CITIES-CLIMATE-CHANGE.pdf
  • Kanters, J., & Horvat, M. (2012). Solar energy as a design parameter in urban planning. In Energy Procedia (Vol. 30, pp. 1143–1152). Elsevier Ltd. doi: 10.1016/j.egypro.2012.11.127
  • Karimi, A., Pahlavani, P., & Bigdeli, B. (2017). Land use analysis on land surface temperature in urban areas using a geographically weighted regression and Landsat 8 imagery, a case study: Tehran, Iran. In International archives of the photogrammetry, remote sensing and spatial information Sciences - ISPRS Archives (Vol. 42, pp. 117–122). International Society for Photogrammetry and Remote Sensing. doi: 10.5194/isprs-archives-XLII-4-W4-117-2017
  • Kasmaee, S., & Tinti, F. (2018). A method to evaluate the impact of urbanization on ground temperature evolution at a regional scale. Rudarsko Geolosko Naftni Zbornik, 33(5), 1–12. doi: 10.17794/rgn.2018.5.1
  • Kaza, N. (2010). Understanding the spectrum of residential energy consumption: A quantile regression approach. Energy Policy, 38(11), 6574–6585. doi: 10.1016/j.enpol.2010.06.028
  • Khamchiangta, D., & Dhakal, S. (2019). Physical and non-physical factors driving urban heat island: Case of Bangkok Metropolitan Administration, Thailand. Journal of Environmental Management, 248, 109285. doi: 10.1016/j.jenvman.2019.109285
  • Ko, Y. (2013). Urban form and residential energy use: A review of design principles and research findings. Journal of Planning Literature, 28(4), 327–351. doi: 10.1177/0885412213491499
  • Kottek, M., Grieser, J., Beck, C., Rudolf, B., & Rubel, F. (2006). World Map of köppen-Geiger climate classification - (updated with CRU TS 2.1 temperature and VASClimO v1.1 precipitation data 1951 to 2000). Meteorologische Zeitschrift, 15(3), 259–263. Retrieved from http://koeppen-geiger.vu-wien.ac.at/shifts.htm. doi: 10.1127/0941-2948/2006/0130
  • Li, X., Zhou, Y., Asrar, G. R., & Zhu, Z. (2018). Developing a 1 km resolution daily air temperature dataset for urban and surrounding areas in the conterminous United States. Remote Sensing of Environment, 215, 74–84. doi: 10.1016/j.rse.2018.05.034
  • Mitchell, G. (2005). Mapping hazard from urban non-point pollution: A screening model to support sustainable urban drainage planning. Journal of Environmental Management, 74(1), 1–9. doi: 10.1016/j.jenvman.2004.08.002
  • Ng, E., & Ren, C. (2018). China’s adaptation to climate & urban climatic changes: A critical review. Urban Climate, 23, 352–372. doi: 10.1016/j.uclim.2017.07.006
  • Oh, M., & Kim, Y. (2019). Identifying urban geometric types as energy performance patterns. Energy for Sustainable Development, 48, 115–129. doi: 10.1016/j.esd.2018.12.002
  • Oke, T. R. (1988). Street design and urban canopy layer climate. Energy and Buildings, 11(1–3), 103–113. doi: 10.1016/0378-7788(88)90026-6
  • Osborne, P. E., & Alvares-Sanches, T. (2019). Quantifying how landscape composition and configuration affect urban land surface temperatures using machine learning and neutral landscapes. Computers, Environment and Urban Systems, 76, 80–90. doi: 10.1016/j.compenvurbsys.2019.04.003
  • Owens, S. E., & Rickaby, P. A. (1992). Settlements and energy revisited. Built Environment, 18(4), 247–252.
  • Resch, E., Bohne, R. A., Kvamsdal, T., & Lohne, J. (2016). Impact of urban density and building height on energy use in cities. In Energy Procedia (Vol. 96, pp. 800–814). Elsevier Ltd. doi: 10.1016/j.egypro.2016.09.142
  • Rodríguez-Álvarez, J. (2016). Urban energy index for buildings (UEIB): A new method to evaluate the effect of urban form on buildings’ energy demand. Landscape and Urban Planning, 148, 170–187. doi: 10.1016/j.landurbplan.2016.01.001
  • Salat, S., Bourdic, L., & Labbe, F. (2014). Breaking symmetries and emerging scaling urban structures: A morphological tale of 3 cities: Paris, New York and Barcelona. Archnet-IJAR, 8(2), 77–93. doi: 10.26687/archnet-ijar.v8i2.445
  • Sattrup, P. A., & Strømann-Andersen, J. (2013). Building typologies in Northern European cities: Daylight, solar access, and building energy use. Journal of Architectural and Planning Research, 30(1), 56–76.
  • Silva, M., Oliveira, V., & Leal, V. (2017). Urban form and energy demand: A review of energy-relevant urban attributes. Journal of Planning Literature, 32(4), 346–365. doi: 10.1177/0885412217706900
  • Sodoudi, S., Shahmohamadi, P., Vollack, K., Cubasch, U., & Che-Ani, A. I. (2014). Mitigating the urban heat island effect in megacity Tehran. Advances in Meteorology, 2014, 1–19. doi: 10.1155/2014/547974
  • Solgi, E., Hamedani, Z., Sherafat, S., Fernando, R., & Aram, F. (2019). The viability of energy auditing in Countries with low energy cost: A case study of a residential building in cold climates. Designs, 3(3), 42. doi: 10.3390/designs3030042
  • Urquizo, J., Calderón, C., & James, P. (2018). Modelling the spatial energy diversity in sub-city areas using remote sensors. In ECOS 2018 - Proceedings of the 31st International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems. University of Minho.
  • Wang, S., Hu, D., Chen, S., & Yu, C. (2019). A partition modeling for anthropogenic heat flux mapping in China. Remote Sensing, 11(9), doi: 10.3390/rs11091132
  • Wetherley, E. B., McFadden, J. P., & Roberts, D. A. (2018). Megacity-scale analysis of urban vegetation temperatures. Remote Sensing of Environment, 213, 18–33. doi: 10.1016/j.rse.2018.04.051
  • Yang, Z., Gupta, K., & Jain, R. K. (2019). Due-A: Data-driven urban energy analytics for understanding relationships between building energy use and urban systems. In Energy Procedia (Vol. 158, pp. 6478–6483). Elsevier Ltd. doi: 10.1016/j.egypro.2019.01.114
  • Ye, H., Ren, Q., Shi, L., Song, J., Hu, X., Li, X., … Xue, X. (2018). The role of climate, construction quality, microclimate, and socio-economic conditions on carbon emissions from office buildings in China. Journal of Cleaner Production, 171, 911–916. doi: 10.1016/j.jclepro.2017.10.099
  • Zhou, Y., Li, Z., & Tao, X. (2016). Urban mixed use and its impact on energy performance of Micro Gird system. In Energy Procedia (Vol. 103, pp. 339–344). Elsevier Ltd. doi: 10.1016/j.egypro.2016.11.296