EUNIS Habitat Maps: Enhancing Thematic and Spatial Resolution for Europe through Machine Learning
Authors/Creators
- Si-Moussi, Sara (Producer)1
-
Hennekens, Stephan
(Producer)2
-
Mucher, Sander
(Producer)2
-
THUILLER, Wilfried
(Producer)1
- De Keersmaecker, Wanda (Data curator)3
- Chytrý, Milan (Data curator)4
- Agrillo, Emiliano (Data curator)5
- Attorre, Fabio (Data curator)6
- Biurrun, Idoia (Data curator)7
- Bonari, Gianmaria (Data curator)8, 9
- Čarni, Andraž (Data curator)10, 11
- Ćušterevska, Renata (Data curator)12
- Dziuba, Tetiana (Data curator)13
- Ecker, Klaus (Data curator)14
- Güler, Behlül (Data curator)15
- Jandt, Ute (Data curator)16, 17
- Jiménez-Alfaro, Borja (Data curator)18
- Lenoir, Jonathan (Data curator)19
- Svenning, Jens-Christian (Data curator)20, 21
- Swacha, Grzegorz (Data curator)22
-
1.
Laboratoire d'Écologie Alpine
-
2.
Wageningen University & Research
-
3.
Flemish Government, Economy, Science and Innovation, Flemish Institute for Technological Research
-
4.
Masaryk University
-
5.
Institute for Environmental Protection and Research
-
6.
Sapienza University of Rome
-
7.
Basque Country University. Plant Biology and Ecology Department
-
8.
University of Siena
- 9. National Biodiversity Future Center (NBFC), Palermo, Italy
-
10.
Jovan Hadži Institute of Biology
-
11.
University of Nova Gorica
-
12.
Saints Cyril and Methodius University of Skopje
-
13.
M.G. Kholodny Institute of Botany
-
14.
Swiss Federal Institute for Forest, Snow and Landscape Research
-
15.
Dokuz Eylül University
-
16.
German Centre for Integrative Biodiversity Research
-
17.
Martin Luther University Halle-Wittenberg
-
18.
Oviedo University
-
19.
Université de Picardie Jules Verne
- 20. Center for Ecological Dynamics in a Novel Biosphere (ECONOVO),
-
21.
Aarhus University
-
22.
University of Business in Wrocław
Contributors
-
1.
Laboratoire d'Écologie Alpine
-
2.
Wageningen University & Research
Description
The EUNIS habitat classification is essential for categorising European habitats and supporting European policy on nature conservation and to implement the Nature Restoration Law. As such, to meet the growing demand for detailed and accurate habitat information, we provide spatial predictions for 260+ EUNIS habitat types at EUNIS level 3, together with validation and uncertainty analyses.
More specifically, using ensemble machine learning models together with high-resolution satellite imagery and other climatic, terrain and soil variables, we produced an European habitat map at a 100-m resolution indicating the most likely EUNIS habitat at level 3 for every location across Europe. Predictions were validated for three independent countries, namely for France, the Netherlands and Austria. We also provide information on uncertainty and the most probable habitats at level 3 within each EUNIS level 1 formation. Products can be further refined with accurate and local land cover data. This product is thus likely to be particularly useful for restoration but also conservation purposes.
Figure: Wall-to-wall map of EUNIS habitats at level 3 - (color coded at level 2 for visibility)
Files
eunis_legend_detailed.csv
Files
(11.9 GB)
| Name | Size | Download all |
|---|---|---|
|
md5:f4037231301c0f29f0dd07fa91b8061e
|
25.4 kB | Download |
|
md5:b9d4921f58edc5aeb6ab31bbfd9a6bc0
|
63.2 kB | Preview Download |
|
md5:783a0fe083365c7c0e79e02f32d4d70a
|
40.7 kB | Download |
|
md5:ccb0223ccda3dfd716a918b724aaf6cc
|
10.3 GB | Preview Download |
|
md5:607802f3033dc902935dd68280054687
|
321.4 kB | Preview Download |
|
md5:c2f48f75bd7d9fb110b30c81caf85fe4
|
7.9 kB | Preview Download |
|
md5:3471958a53bdd9cad13f34ceb028d6ca
|
1.4 GB | Preview Download |
|
md5:5fd268a6d0a644eaab33466598635578
|
234.7 MB | Preview Download |