IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0246096.html
   My bibliography  Save this article

Machine learning for buildings’ characterization and power-law recovery of urban metrics

Author

Listed:
  • Alaa Krayem
  • Aram Yeretzian
  • Ghaleb Faour
  • Sara Najem

Abstract

In this paper we focus on a critical component of the city: its building stock, which holds much of its socio-economic activities. In our case, the lack of a comprehensive database about their features and its limitation to a surveyed subset lead us to adopt data-driven techniques to extend our knowledge to the near-city-scale. Neural networks and random forests are applied to identify the buildings’ number of floors and construction periods’ dependencies on a set of shape features: area, perimeter, and height along with the annual electricity consumption, relying a surveyed data in the city of Beirut. The predicted results are then compared with established scaling laws of urban forms, which constitutes a further consistency check and validation of our workflow.

Suggested Citation

  • Alaa Krayem & Aram Yeretzian & Ghaleb Faour & Sara Najem, 2021. "Machine learning for buildings’ characterization and power-law recovery of urban metrics," PLOS ONE, Public Library of Science, vol. 16(1), pages 1-13, January.
    • Handle: RePEc:plo:pone00:0246096
    DOI: 10.1371/journal.pone.0246096
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0246096
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0246096&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0246096?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. M. Batty & R. Carvalho & A. Hudson-Smith & R. Milton & D. Smith & P. Steadman, 2008. "Scaling and allometry in the building geometries of Greater London," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 63(3), pages 303-314, June.
    2. Ravetz, Joe, 2008. "State of the stock--What do we know about existing buildings and their future prospects?," Energy Policy, Elsevier, vol. 36(12), pages 4462-4470, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Foulds, Chris & Powell, Jane, 2014. "Using the Homes Energy Efficiency Database as a research resource for residential insulation improvements," Energy Policy, Elsevier, vol. 69(C), pages 57-72.
    2. Azevedo, Isabel & Delarue, Erik & Meeus, Leonardo, 2013. "Mobilizing cities towards a low-carbon future: Tambourines, carrots and sticks," Energy Policy, Elsevier, vol. 61(C), pages 894-900.
    3. Altwies, Joy E. & Nemet, Gregory F., 2013. "Innovation in the U.S. building sector: An assessment of patent citations in building energy control technology," Energy Policy, Elsevier, vol. 52(C), pages 819-831.
    4. Chen, Yanguang, 2015. "The distance-decay function of geographical gravity model: Power law or exponential law?," Chaos, Solitons & Fractals, Elsevier, vol. 77(C), pages 174-189.
    5. Krzysztof Cebrat & Maciej Sobczyński, 2016. "Scaling Laws in City Growth: Setting Limitations with Self-Organizing Maps," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-11, December.
    6. Ballarini, Ilaria & Corgnati, Stefano Paolo & Corrado, Vincenzo, 2014. "Use of reference buildings to assess the energy saving potentials of the residential building stock: The experience of TABULA project," Energy Policy, Elsevier, vol. 68(C), pages 273-284.
    7. Haosu Zhao & Bart Julien Dewancker & Feng Hua & Junping He & Weijun Gao, 2020. "Restrictions of Historical Tissues on Urban Growth, Self-Sustaining Agglomeration in Walled Cities of Chinese Origin," Sustainability, MDPI, vol. 12(14), pages 1-29, July.
    8. Deakin, Mark & Campbell, Fiona & Reid, Alasdair, 2012. "The mass-retrofitting of an energy efficient-low carbon zone: Baselining the urban regeneration strategy, vision, masterplan and redevelopment scheme," Energy Policy, Elsevier, vol. 45(C), pages 187-200.
    9. Chen, Yanguang, 2017. "Multi-scaling allometric analysis for urban and regional development," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 673-689.
    10. Balta-Ozkan, Nazmiye & Davidson, Rosemary & Bicket, Martha & Whitmarsh, Lorraine, 2013. "The development of smart homes market in the UK," Energy, Elsevier, vol. 60(C), pages 361-372.
    11. Wang, Huan & Chen, Wenying & Shi, Jingcheng, 2018. "Low carbon transition of global building sector under 2- and 1.5-degree targets," Applied Energy, Elsevier, vol. 222(C), pages 148-157.
    12. Pierpaolo Andriani & Bill McKelvey, 2009. "Perspective ---From Gaussian to Paretian Thinking: Causes and Implications of Power Laws in Organizations," Organization Science, INFORMS, vol. 20(6), pages 1053-1071, December.
    13. Zhang, Lin, 2013. "Model projections and policy reviews for energy saving in China's service sector," Energy Policy, Elsevier, vol. 59(C), pages 312-320.
    14. Asaf Friedman Arch, 2014. "Sustainable Urban Renewal: The Tel Aviv Dilemma," Sustainability, MDPI, vol. 6(5), pages 1-11, April.
    15. Daniel Czamanski & Rafael Roth, 2011. "Characteristic time, developers’ behavior and leapfrogging dynamics of high-rise buildings," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 46(1), pages 101-118, February.
    16. Futcher, Julie Ann & Mills, Gerald, 2013. "The role of urban form as an energy management parameter," Energy Policy, Elsevier, vol. 53(C), pages 218-228.
    17. Melo, A.P. & Cóstola, D. & Lamberts, R. & Hensen, J.L.M., 2014. "Development of surrogate models using artificial neural network for building shell energy labelling," Energy Policy, Elsevier, vol. 69(C), pages 457-466.
    18. Hiroyuki Usui, 2024. "Relative spatial variability in building heights and its spatial association: Application for the spatial clustering of harmonious and inharmonious building heights in Tokyo," Environment and Planning B, , vol. 51(4), pages 987-1002, May.
    19. Paul J. Maliszewski & Breandán Ó hUallacháin, 2012. "Hierarchy and concentration in the American urban system of technological advance," Papers in Regional Science, Wiley Blackwell, vol. 91(4), pages 743-758, November.
    20. Owen, A. & Mitchell, G. & Gouldson, A., 2014. "Unseen influence—The role of low carbon retrofit advisers and installers in the adoption and use of domestic energy technology," Energy Policy, Elsevier, vol. 73(C), pages 169-179.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0246096. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.