task_categories:image-segmentation task_categories:image-feature-extraction language:en license:apache-2.0 size_categories:n<1K format:imagefolder modality:image library:datasets library:mlcroissant region:us climate
---
license: apache-2.0
task_categories:
- image-segmentation
- image-feature-extraction
language:
- en
tags:
- climate
pretty_name: d
size_categories:
- 100M<n<1B
---

Manual crown delineation of individual trees in two countries: Denmark and Finland.


Dataset download link: https://sid.erda.dk/sharelink/eFt21tspNe

GitHub page: https://github.com/sizhuoli/TreeCountSegHeight

Publication: https://doi.org/10.1093/pnasnexus/pgad076


----------------------------------------


Dataset description: 

---------- Denmark data---------- :

More than 20k individual trees growing in different landscapes.

Annotation masks are paired with aerial photographs with a spatial resolution of 20cm.

Images contain RGB and near-infrared bands and were taken in summer 2018.

Image credits: Danish Agency for Data Supply and Infrastructure (https://sdfi.dk/)

---------- Finland data---------:

More than 4k individual tree crowns in random sampling regions

Annotation masks are paired with aerial photographs containing near-infrared, green, and blue bands with a spatial resolution of 50cm

Image credits: National Survey of Finland (https://www.maanmittauslaitos.fi/en/maps-and-spatial-data)



Tasks:

Segmentation of individual tree crowns

Transfer learning/domain adaptation between datasets with different visual semantics, band compositions, forest species, etc.


