Using change detection data to assess amount and composition of demolition waste from buildings in Vienna

Major waste streams in urban areas result from the demolition of buildings. In the case of lack of data ondemolition waste generation at the municipal level, the quantity and composition of demolition wastesfrom buildings can be estimated by multiplying the volume of demolished buildings, which is takenfrom statistical data sets, by their material composition. However, statistical data sets about the numberand thus total volume of buildings demolished are often incomplete. This paper presents an alternativeapproach to validating demolition statistics (number and volume of buildings demolished) and subse-quently demolition waste generation by applying change detection based on image matching to the casestudy of the city of Vienna, Austria. Based on this technique, building demolition activities not reportedto statistical municipal departments can be identified. Results show that in the city of Vienna, demolitionstatistics yield a total volume of 1.7 M m3/a demolished building volume, while change detection basedon image matching yields a total volume of 2.8 M m3/a. Consequently, demolition waste generation fig-ures solely based on statistical data probably underestimate the total waste generation, which can havesignificant consequences for the estimation of landfill space and recycling plant capacity required. Forthis reason, the approach presented is not only a useful tool for validating existing data on demolitionwaste generation and demolition statistics, but can also be used when these data sets are not existent atall.

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