Component-Level Residential Building Material Stock Characterization Using Computer Vision Techniques-Reference-Cited by-同舟云学术

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Component-Level Residential Building Material Stock Characterization Using Computer Vision Techniques

Published:2024-02-09 Issue: Volume: Page:
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Dai Menglin¹^ORCID,Jurczyk Jakub²,Arbabi Hadi²,Mao Ruichang³^ORCID,Ward Wil²,Mayfield Martin²,Liu Gang¹,Tingley Danielle Densley²

Affiliation:

1. College of Urban and Environmental Sciences, Peking University, Beijing 100871, China

2. Department of Civil and Structural Engineering, The University of Sheffield, Sheffield S1 3JD, U.K.

3. Department of Environmental and Resource Engineering, Technical University of Denmark, Kgs Lyngby 2800, Denmark

Funder

Engineering and Physical Sciences Research Council

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.3c09207

Reference66 articles.

1. International Energy Agency. Tracking Clean Energy Progress 2023, 2023. License: CC BY 4.0.

2. United Nations. Sustainable Development Goals, 2015. https://www.un.org/sustainabledevelopment/sustainable-development-goals/ (accessed 06 06, 2023).

3. Global human-made mass exceeds all living biomass

4. Global socioeconomic material stocks rise 23-fold over the 20th century and require half of annual resource use

5. Embed circular economy thinking into building retrofit

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