---
license: other
license_name: prosperity-public-license-3.0.0
license_link: LICENSE
task_categories:
- image-classification
- image-segmentation
- image-feature-extraction
language:
- en
---
# DeepTrees Halle DOP20 labels + imagery

[![DOI](https://huggingface.co/datasets/huggingface/badges/resolve/main/dataset-on-hf-sm.svg)](https://doi.org/10.57967/hf/4213)


This is a sample dataset for model training and fine-tuning in tree crown segmentation tasks using the [DeepTrees](https://deeptrees.de) Python package. 

Overview of subtiles with sample of labels:

![image/png](https://cdn-uploads.huggingface.co/production/uploads/678d3a445e6af698f2d2ce30/cz3J6SjUuApXww7BuXH30.png)

## Dataset Details

We have taken a single Multispectral (RGBi) 2x2 km DOP20 image tile for Halle, Sachsen-Anhalt, from LVermGeo ST for the year of 2022. 

**TileID from source:** 32_704_5708_2

We then sliced the tiles into subtiles of 100x100m, resulting in 400 subtiles. These are provided as 4-band raster `.tif` files.

We are manually labelling tree crowns in these subtiles based on an entropy-based active learning approach. The label classes have been provided below. 

The labeling is done in QGIS and the polygon vectors are provided as  ESRI-shape `.shp` files per subtile.

### Label Classes

**0** = tree

**1** = cluster of trees

**2** = unsure

**3** = dead trees (haven’t added yet)


### Dataset Description

- **Curated by:** Taimur Khan
- **Funded by:** Helmholtz Center for Environmental Research - UFZ
- **Contact:** [taimur.khan@ufz.de](mailto:taimur.khan@ufz.de)

### Cite the dataset

```
@misc {taimur_khan_2025,
	author       = { {Taimur Khan} },
	title        = { DeepTrees_Halle (Revision 0c528b9) },
	year         = 2025,
	url          = { https://huggingface.co/datasets/thisistaimur/DeepTrees_Halle },
	doi          = { 10.57967/hf/4213 },
	publisher    = { Hugging Face }
}
```

### License

This repository is made avaiable under The Prosperity Public License 3.0.0. A copy of the license can be found in the [LICENSE.md](LICENSE.md) file.


### References

- Halle DOP20: © [GeoBasis-DE / LVermGeo ST 2022](https://www.lvermgeo.sachsen-anhalt.de/de/gdp-digitale-orthophotos.html)