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Publication

Multi-Resolution Remote Sensing Dataset for the Detection of Anthropogenic Litter: A Multi-Platform and Multi-Sensor Approach

Robert Rettig; Felix Becker; Alexander Berghoff; Tobias Binkele; Wolfram Michael Butter; Tilman Floehr; Martin Krumm; Carolin Leluschko; Florian Littau; Elmar Reinders; Eike Rodenbäck; Tobias Schmid; Sabine Schründer; Sören Schweigert; Michael Sinhuber; Jens Wellhausen; Frederic Theodor Stahl; Christoph Tholen
In: Data (Data), Vol. 10, No. 7, Pages 1-10, MDPI, Basel, 7/2025.

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 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.