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Area of Science:

  • Built Environment Analysis
  • Sustainable Materials Science
  • Geospatial Data Science

Background:

  • Residential building material stock is a significant component of the built environment.
  • Previous research focused on spatial analysis of building mass, neglecting component-level stock and requiring costly surveys.
  • Accurate characterization of building materials is essential for resource management and circular economy initiatives.

Purpose of the Study:

  • To develop an efficient, component-level method for residential building material stock accounting in the UK.
  • To utilize drive-by street view images and building footprint data for material mass estimation.
  • To provide a basis for evaluating material reuse potential and supporting circular economy objectives.

Main Methods:

  • Developed a novel approach for component-level residential building stock accounting.
  • Utilized drive-by street view images and building footprint data.
  • Employed automatically extracted physical dimensions and predicted material types to calculate mass for brick, stone, mortar, and glass.

Main Results:

  • Achieved error rates of 5% for mortar, 22% for glass, 8% for brick, and 7% for stone mass estimations.
  • Demonstrated improved efficiency and accuracy compared to traditional methods.
  • Validated results for known wall types, highlighting the method's reliability.

Conclusions:

  • The developed method offers significant advancements in building material stock characterization.
  • The approach enhances efficiency and accuracy in managing diverse building structures.
  • This methodology provides a foundation for assessing component-level material reuse, aligning with circular economy principles.