Border Region Austria - Slovakia around Bratislava

EuroCrops

EuroCrops is a dataset collection combining all publicly available self-declared crop reporting datasets from countries of the European Union. The project is funded by the German Space Agency at DLR on behalf of the Federal Ministry for Economic Affairs and Climate Action (BMWK). This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Right now EuroCrops only includes vector data, but stay tuned for a version that includes satellite imagery!

For any questions, please refer to our FAQs or use the Discussions/Issues to reach out to us.

Content

1. Background
2. Hamonisation with HCAT
3. Participating countries
4. GitHub project structure
5. Vector data download via zenodo
6. Vector data download via Sync&Share (old)
7. Reference

Background

Disclaimer: The Nomenclature of Territorial Units for Statistics 3 (NUTS3) region, which we added by hand, is just an approximate assignment of a crop parcel to a region. It might happen that a parcel is not correctly allocated to the right region or country. The NUTS3 attribute is only meant to be an aid for a meaningful spatial division of the dataset into training, validation and test sets.

Hamonisation with HCAT

The raw data obtained from the countries does not come in a unified, machine-readable taxonomy. We, therefore, developed a new Hierarchical Crop and Agriculture Taxonomy (HCAT) that harmonises all declared crops across the European Union. In the shapefiles you'll find this as additional attributes:

Participating countries

Find detailed information for all countries of the European Union in our Wiki, especially the countries represented in EuroCrops:

• Austria
• Belgium
• Czechia
• Germany
• Denmark
• Estonia
• Spain
• France
• Croatia
• Lithuania
• Latvia
• Netherlands
• Portugal
• Romania
• Sweden
• Slovenia
• Slovakia

GitHub project structure

├── csvs
│   ├── country_mappings
│       └── [CSV mapping files for all participating countries]
└── hcat_core
    └── HCAT.csv

Vector data download via zenodo

The vector data is now available via zenodo, currently we are on Version 9!

Vector data download via Sync&Share (only Version 1)

The shapefiles of the countries are available via Sync&Share. Please also make sure to download the data for the countries individually, as there might be some loss otherwise.

├── AT
│   └── AT_2021_EC21.*
├── BE
│   └── VLG
│       └── BE_VLG_2021_EC21.*
├── DE
│   ├── LS
│   |   └── DE_LS_2021_EC21.*
│   └── NRW
│       └── DE_NRW_2021_EC21.*
├── DK
│   └── DK_2019_EC21.*
├── EE
│   └── EE_2021_EC21.*
├── ES
│   └── NA
│       └── ES_NA_2020_EC21.*
├── FR
│   └── FR_2018_EC21.*
├── HR
│   └── HR_2020_EC21.*
├── LT
│   └── LT_2021_EC.*
├── LV
│   └── LV_2021_EC21.*
├── NL
│   └── NL_2021_EC21.*
├── PT
│   └── PT_2021_EC21.*
├── RO
│   └── RO_ny_EC21.*
├── SE
│   └── SE_2021_EC21.*
├── SI
│   └── SI_2021_EC21.*
└── SK
    └── SK_2021_EC21.*

Reference

Disclaimer: Please reference the countries' dependent source in case you're using their data.

@Article{schneider2023eurocrops,
	title = {{EuroCrops}: {The} {Largest} {Harmonized} {Open} {Crop} {Dataset} {Across} the {European} {Union}},
	volume = {10},
	copyright = {All rights reserved},
	issn = {2052-4463},
	url = {https://doi.org/10.1038/s41597-023-02517-0},
	doi = {10.1038/s41597-023-02517-0},
	number = {1},
	journal = {Scientific Data},
	author = {Schneider, Maja and Schelte, Tobias and Schmitz, Felix and Körner, Marco},
	month = sep,
	year = {2023},
	pages = {612},
}

Additional references:

@Misc{schneider2022eurocrops21,
 author     = {Schneider, Maja and K{\"o}rner, Marco},
 title      = {EuroCrops},
 DOI        = {10.5281/zenodo.6866846},
 type       = {Dataset},
 publisher  = {Zenodo},
 year       = {2022}
}

@InProceedings{Schneider2022Challenges,
  title     = {Challenges and Opportunities of Large Transnational Datasets: A Case Study on European Administrative Crop Data},
  author    = {Schneider, Maja and Marchington, Christian and K{\"o}rner, Marco},
  booktitle = {Workshop on Broadening Research Collaborations in ML (NeurIPS 2022)},
  year      = {2022}
}

@InProceedings{Schneider2022Harnessing,
  title         = {Harnessing Administrative Data Inventories to Create a Reliable Transnational Reference Database for Crop Type Monitoring},
  author        = {Schneider, Maja and K{\"o}rner, Marco},
  booktitle     = {IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium},
  pages         = {5385--5388},
  year          = {2022},
  organization  = {IEEE}
}

@InProceedings{Schneider2021EPE,
  author        = {Schneider, Maja and Broszeit, Amelie and K{\"o}rner, Marco},
  booktitle     = {Proceedings of the Conference on Big Data from Space (BiDS)},
  title         = {{EuroCrops}: A Pan-European Dataset for Time Series Crop Type Classification},
  editor        = {Soille, Pierre and Loekken, Sveinung and Albani, Sergio},
  publisher     = {Publications Office of the European Union},
  date          = {2021-05-18},
  doi           = {10.2760/125905},
  eprint        = {2106.08151},
  eprintclass   = {eess.IV,cs.CV,cs.LG},
  eprinttype    = {arxiv}
}

@Misc{Schneider2021TEC,
  author       = {Schneider, Maja and K{\"o}rner, Marco},
  date         = {2021-06-15},
  title        = {{TinyEuroCrops}},
  doi          = {10.14459/2021MP1615987},
  organization = {Technical University of Munich (TUM)},
  type         = {Dataset},
  url          = {https://mediatum.ub.tum.de/1615987}
}