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Spatial and Temporal Characteristics and Prediction of C&DW in Shenzhen

In: Proceedings of the 26th International Symposium on Advancement of Construction Management and Real Estate

Author

Listed:
  • Meiqin Xiong

    (Sino-Australia Joint Research Center in BIM and Smart Construction, Shenzhen University)

  • Clyde Zhengdao Li

    (Sino-Australia Joint Research Center in BIM and Smart Construction, Shenzhen University
    Shenzhen University
    Shenzhen University)

  • Bing Xiao

    (Western Sydney University)

  • Vivian W. Y. Tam

    (Western Sydney University)

  • Shanyang Li

    (Shenzhen University)

  • Zhenchao Guo

    (Shenzhen University)

Abstract

Recently, with the acceleration of urbanization and the increase of construction and demolition waste (C&DW) production, the research on C&DW management has been paid more attention. To optimize C&DW management, it is essential to accurately obtain information on the quantity, time, location and flow direction of waste generated. In this study, a prediction model of C&DW production was established based on the yield method per unit floor area. With the help of Google Earth software and corresponding database to collect and process data, the waste production of Shenzhen city from 2021 to 2030 is predicted by using GIS and grey prediction method, to complete the prediction of the temporal and spatial distribution of the waste production. Reasonable prediction results of C&DW can provide valuable reference information for waste resource utilization, to realize efficient and sustainable waste management.

Suggested Citation

  • Meiqin Xiong & Clyde Zhengdao Li & Bing Xiao & Vivian W. Y. Tam & Shanyang Li & Zhenchao Guo, 2022. "Spatial and Temporal Characteristics and Prediction of C&DW in Shenzhen," Lecture Notes in Operations Research, in: Hongling Guo & Dongping Fang & Weisheng Lu & Yi Peng (ed.), Proceedings of the 26th International Symposium on Advancement of Construction Management and Real Estate, pages 284-294, Springer.
    • Handle: RePEc:spr:lnopch:978-981-19-5256-2_23
    DOI: 10.1007/978-981-19-5256-2_23
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