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Hyperspectral longwave infrared reflectance spectra of dryanthropogenic plastics and natural materials
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Researchers measured directional hemispherical reflectance spectra of plastic debris and natural materials from Chilean beaches using a thermal infrared hyperspectral spectrometer. The resulting spectral library identifies diagnostic wavelengths for distinguishing plastic types from natural beach materials, supporting remote sensing of coastal plastic pollution.
Abstract. Remote sensing of litter is foreseen to be an important source of additional information relevant to scientific awareness about plastic pollution. Here, we document directional hemispherical reflectance measurements of anthropogenic and natural materials gathered along the shorelines of Chiloé Archipelago, Chile. These spectral observations were completed in a laboratory using a state-of-the-art hyperspectral HyLogger-3™ spectrometer in the thermal infrared (TIR) region; medium wave infrared (6000 nm) to long wave infrared (14 500 nm) spectrum at 25 nm intervals. The samples we investigated included sands, shells, algae, nautical ropes, Styrofoam®, gunny sacks and several fragments of plastic based items. The visible colours of these samples included shades of black, blue, brown, green, orange, white and yellow. We grouped the samples using robust statistical approaches (derivatives, peak seeking technique) and visual analyses of the derived hyperspectral reflectances. In each group we derived the average or TIR end-member signal as well as deduced diagnostic wavebands. Most of the diagnostic wavebands picked were found to be inside the atmospheric window of the TIR spectrum region. Furthermore, this laboratory reference dataset and findings might become useful in related field observations using similar thermal infrared technologies, especially in identifying anomalies resulting from environmental and meteorological perturbations. Validation and verification of proposed diagnostic wavebands would be part of a continuing effort to advance TIR remote sensing knowledge as well as assist robust detection algorithm development to potentially distinguish plastics in litter throughout the natural environments. Data is available in open-access via the online repository PANGAEA database of the World Data Centre for Marine Environmental Sciences https://doi.pangaea.de/10.1594/PANGAEA.919536 (Acuña-Ruz and Mattar B., 2020).
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