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

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

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 addre...

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Bibliographic Details
Main Authors: 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, Christoph Tholen
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Data
Subjects:
anthropogenic litter
plastic litter pollution
litter object detection
dataset annotation
multi-resolution
multi-sensor
Online Access:https://www.mdpi.com/2306-5729/10/7/113
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Summary: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.
ISSN:2306-5729

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