Journal
RESOURCES CONSERVATION AND RECYCLING
Volume 123, Issue -, Pages 37-46Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.resconrec.2016.06.010
Keywords
Construction and demolition waste; Demolition waste generation; Urban mining; Image matching; Change detection; GIS
Categories
Funding
- Wiener Stadtbaudirektion - Gruppe Umwelttechnik und behordliche Verfahren
- Federal Ministry of Science, Research, and Economy
- National Foundation for Research, Technology and Development
- Altstoff Recycling Austria AG (ARA)
- Borealis group
- voestalpine AG
- Wien Energie GmbH
- Wiener Kommunal-Umweltschutzprojektgesellschaft GmbH
- Wiener Linien GmbH Co KG
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Major waste streams in urban areas result from the demolition of buildings. In the case of lack of data on demolition waste generation at the municipal level, the quantity and composition of demolition wastes from buildings can be estimated by multiplying the volume of demolished buildings, which is taken from statistical data sets, by their material composition. However, statistical data sets about the number and thus total volume of buildings demolished are often incomplete. This paper presents an alternative approach to validating demolition statistics (number and volume of buildings demolished) and subsequently demolition waste generation by applying change detection based on image matching to the case study of the city of Vienna, Austria. Based on this technique, building demolition activities not reported to statistical municipal departments can be identified. Results show that in the city of Vienna, demolition statistics yield a total volume of 1.7 M m(3)/a demolished building volume, while change detection based on image matching yields a total volume of 2.8 M m(3)/a. Consequently, demolition waste generation figures solely based on statistical data probably underestimate the total waste generation, which can have significant consequences for the estimation of landfill space and recycling plant capacity required. For this reason, the approach presented is not only a useful tool for validating existing data on demolition waste generation and demolition statistics, but can also be used when these data sets are not existent at all. (C) 2016 Elsevier B.V. All rights reserved.
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