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--- |
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license: apache-2.0 |
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task_categories: |
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- image-segmentation |
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- image-feature-extraction |
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language: |
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- en |
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tags: |
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- climate |
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pretty_name: d |
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size_categories: |
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- 100M<n<1B |
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--- |
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# Manual crown delineation of individual trees in 2 countries: Denmark and Finland |
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Dataset download link: https://sid.erda.dk/sharelink/eFt21tspNe |
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GitHub page: https://github.com/sizhuoli/TreeCountSegHeight |
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Publication: https://doi.org/10.1093/pnasnexus/pgad076 |
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---------------------------------------- |
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## Dataset description |
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---------- **Denmark data**---------- : |
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More than 20k individual trees growing in different landscapes. |
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Annotation masks are paired with aerial photographs with a spatial resolution of 20cm. |
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Images contain RGB and near-infrared bands and were taken in summer 2018. |
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Image credits: Danish Agency for Data Supply and Infrastructure (https://sdfi.dk/) |
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---------- **Finland data**---------: |
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More than 4k individual tree crowns in random sampling regions |
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Annotation masks are paired with aerial photographs containing near-infrared, green, and blue bands with a spatial resolution of 50cm |
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Image credits: National Survey of Finland (https://www.maanmittauslaitos.fi/en/maps-and-spatial-data) |
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## Tasks |
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* Segmentation of individual tree crowns |
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* Transfer learning/domain adaptation between datasets with different visual semantics, band compositions, forest species, etc. |
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## Citation |
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``` |
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@article{li2023deep, |
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title={Deep learning enables image-based tree counting, crown segmentation, and height prediction at national scale}, |
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SHORTauthor={Li, Sizhuo and Brandt, Martin and Fensholt, Rasmus and Kariryaa, Ankit and Igel, Christian and Gieseke, Fabian and Nord-Larsen, Thomas and Oehmcke, Stefan and Carlsen, Ask Holm and Junttila, Samuli and others}, |
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author={Li, Sizhuo and Brandt, Martin and Fensholt, Rasmus and Kariryaa, Ankit and Igel, Christian and Gieseke, Fabian and Nord-Larsen, Thomas and Oehmcke, Stefan and Carlsen, Ask Holm and Junttila, Samuli and Xiaoye Tong and Alexandre d’Aspremont and Philippe Ciais}, |
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journal={PNAS nexus}, |
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volume={2}, |
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number={4}, |
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year={2023}, |
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publisher={Oxford University Press} |
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} |
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