Dataset for object detection of charcoal production sites

Type of the data
datacite.resourceTypeGeneral

Dataset

Type of the data
datacite.resourceTypeGeneral

Model

Type of the data
datacite.resourceTypeGeneral

Image

Total size of the dataset
datacite.size

2202967815

Author
dc.contributor.author

Rünger, Carolin

Author
dc.contributor.author

Neubauer, Grit

Author
dc.contributor.author

Zamboni, Pedro

Author
dc.contributor.author

Van der Maaten-Theunissen, Marieke

Author
dc.contributor.author

Eltner, Anette

Upload date
dc.date.accessioned

2025-12-18T12:43:53Z

Publication date
dc.date.available

2025-12-18T12:43:53Z

Publication date
dc.date.issued

2025-12-18

Abstract of the dataset
dc.description.abstract

This dataset provides a collection of processed airborne LiDAR data and associated annotations of historical charcoal production sites in the Erzgebirge district of Saxony, Germany for object detection. Using official files from the digital terrain model (DTM), various DTM derivatives were calculated and used as three-channel input data (hillshade, slope and sky-view factor) for a convolutional neural network. The dataset includes training, validation and test data, including annotations, as well as trained model weights and configuration files for inference. To ensure reproducibility, the suitable Conda environment for training and inference with MMDetection v2.28.2 is also provided.

Public reference to this page
dc.identifier.uri

https://opara.zih.tu-dresden.de/handle/123456789/1914

Public reference to this page
dc.identifier.uri

https://doi.org/10.25532/OPARA-1051

Publisher
dc.publisher

Technische Universität Dresden

Licence
dc.rights

Attribution-NonCommercial-ShareAlike 4.0 Internationalen

URI of the licence text
dc.rights.uri

http://creativecommons.org/licenses/by-nc-sa/4.0/

Specification of the discipline(s)
dc.subject.classification

3::34::315::315-02

Specification of the discipline(s)
dc.subject.classification

2::23::207::207-06

Title of the dataset
dc.title

Dataset for object detection of charcoal production sites

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