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Multi-Resolution Remote Sensing Dataset for the Detection of Anthropogenic Litter: A Multi-Platform and Multi-Sensor Approach
by
Robert Rettig, Felix Becker, Alexander Berghoff, Tobias Binkele, Wolfram Michael Butter, Tilman Floehr, Martin Kumm, Carolin Leluschko, Florian Littau, Elmar Reinders, Eike Rodenbäck, Tobias Schmid, Sabine Schründer, Sören Schweigert, Michael Sinhuber, Jens Wellhausen, Frederic Stahl and Christoph Tholen
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Abstract
The dataset developed within the PlasticObs+ project aims to facilitate a multi-resolution approach for detecting and quantifying anthropogenic litter through areal images. Traditional detection methods often suffer from narrow, use-case-specific limitations, reducing their transferability. To address this, an image dataset was created featuring
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The dataset developed within the PlasticObs+ project aims to facilitate a multi-resolution approach for detecting and quantifying anthropogenic litter through areal images. Traditional detection methods often suffer from narrow, use-case-specific limitations, reducing their transferability. To address this, an image dataset was created featuring various spatial and spectral resolutions. The highest spatial resolution images (ground sampling distance = 0.2 cm) were used to generate a labeled dataset, which was georeferenced for mapping onto coarser-resolution images.
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