Characterization of post-earthquake construction and demolition wastes by Hyperspectral imaging

Earthquakes create significant volumes of rubbles and waste (CDWs- Construction and Demolition Wastes), strongly impacting the environment and posing health risks. This paper investigates an automatic sensor-based approach finalized to identify and classify different postdisaster CDWs in order to be recycled as secondary raw material. The investigated CDWs were generated at Amatrice and Norcia areas (central Italy) in 2016 and 2017. The study presents a methodology based on a combination of two analytical techniques, HyperSpectral Imaging (HSI) in the SWIR range (1000-2500 nm) and X-ray fluorescence (XRF), in order to discriminate different samples compositions – e.g. Concretes, Roof Tiles, Bricks, as well as the recognition of contaminants – e.g. cement matrix on the surface of the samples. Results can represent an important starting point for further development of fully optical HSI based recognition CDWs procedures to be utilized both off-line (i.e. laboratory scale) and on-line (i.e. sorting level at industrial scale).