SoilHealthDataCube
Soil Health Data Cube for Europe.
https://github.com/ai4soilhealth/soilhealthdatacube
Category: Natural Resources
Sub Category: Soil and Land
Last synced: about 12 hours ago
JSON representation
Repository metadata
Soil Health Data Cube for Europe
- Host: GitHub
- URL: https://github.com/ai4soilhealth/soilhealthdatacube
- Owner: AI4SoilHealth
- License: mit
- Created: 2023-06-26T07:39:14.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-07-24T13:36:40.000Z (7 months ago)
- Last Synced: 2026-01-21T23:40:38.305Z (16 days ago)
- Language: Jupyter Notebook
- Size: 75.9 MB
- Stars: 14
- Watchers: 2
- Forks: 3
- Open Issues: 1
- Releases: 5
-
Metadata Files:
- Readme: README.md
- License: LICENSE
README.md
Soil Health Data Cube
The Soil Health Data Cube for Europe provides technical documentation and computational notebooks to support soil health monitoring across Europe.
- Data License: CC-BY (unless stated otherwise)
- Code License: MIT License
For detailed technical information, see the Soil Health Data Cube for Europe Technical Manual.
Repository Contents
1. paneu_landmask
This folder contains files used to produce three Pan-EU land masks:
-
Jupyter Notebook (Tile Products):
- Land Mask: Differentiates land, ocean, and inland water
- NUT-3 Code Map: Administrative areas at the NUT-3 level
- ISO-3166 Country Code Map: Countries coded according to ISO-3166 standard
-
Bash Scripts:
- Merge tiles, reproject CRS, and resample to different resolutions
All land masks follow AI4SoilHealth Work Package 5 standards and align with data coverage from Copernicus Pan-European Land Service, closely matching the official EEA39 countries.
This landmask serves as a reference for landmask, spatial content, and resolution for all data products in this repository.
Contacts
2. landsat_based_spectral_indices
A time-series of Landsat-based spectral indices (2000–2022) for continental Europe (including Ukraine, the UK, and Turkey).
- Resolution: 30 meters
- Temporal Coverage: Bi-monthly, annual, and long-term analyses
- Applications:
- Vegetation cover monitoring
- Soil exposure assessment
- Tillage and crop intensity analysis
- Input for soil property modeling
Publication / Citation
Tian, X., Consoli, D., Witjes, M., Schneider, F., Parente, L., Şahin, M., Ho, Y.-F., Minařík, R., and Hengl, T. (2025):
Time series of Landsat-based bimonthly and annual spectral indices for continental Europe for 2000–2022.
Earth Syst. Sci. Data, 17, 741–772. https://doi.org/10.5194/essd-17-741-2025
Indices Provided
- Vegetation: NDVI, SAVI, FAPAR
- Soil Exposure: Bare Soil Fraction (BSF)
- Tillage & Soil Sealing: NDTI, minNDTI
- Crop Patterns: Number of Seasons (NOS), Crop Duration Ratio (CDR)
- Water Dynamics: NDSI, NDWI
Production Workflow
Example
Bare Soil Fraction (%) time series for Europe (2000–2022):
Complete Access Catalog
Google Spreadsheet Catalog
3. SOCD_map
Contains notebooks and scripts for predictive modeling of soil organic carbon density (SOCD):
- Notebooks (001–009): Testing various steps in the predictive modeling workflow
- Benchmark Pipeline Script:
benchmark_pipeline.pyautomates model building - Property-Specific Modeling (010–011): Loops pipeline across soil properties
- Prediction Interval Models (012–014): Adds uncertainty quantification
Publication / Citation
Tian, X., de Bruin, S., Simoes, R., Isik, M.S., Minarik, R., Ho, Y., Şahin, M., Herold, M., Consoli, D., and Hengl, T. (2025):
Spatiotemporal prediction of soil organic carbon density in Europe (2000–2022) using earth observation and machine learning.
PeerJ, 13:e19605. https://doi.org/10.7717/peerj.19605
4. soil_property_model_pipeline
Implements the tested pipeline from SOCD_map to predict 10 key soil properties, with the resulting maps available at https://ecodatacube.eu.
5. WRB_map
Scripts to test, train, and evaluate predictive models for mapping soil types based on the IUSS World Reference Base (WRB) classification.
Acknowledgments & Funding
This work is part of the AI4SoilHealth project, funded by the European Union's Horizon Europe Research and Innovation Programme under Grant Agreement No. 101086179.
Funded by the European Union. The views expressed are those of the authors and do not necessarily reflect those of the European Union or the European Research Executive Agency.
Owner metadata
- Name: AI4SoilHealth Horizon Europe project
- Login: AI4SoilHealth
- Email: tom.hengl@opengeohub.org
- Kind: organization
- Description: Horizon Europe Grant Agreement No. 101086179. 2022–2026
- Website: https://ai4soilhealth.eu
- Location: Netherlands
- Twitter: AI4SoilHealth
- Company:
- Icon url: https://avatars.githubusercontent.com/u/137761643?v=4
- Repositories: 1
- Last ynced at: 2023-07-06T12:28:36.353Z
- Profile URL: https://github.com/AI4SoilHealth
GitHub Events
Total
- Create event: 2
- Issues event: 3
- Release event: 2
- Watch event: 7
- Issue comment event: 2
- Push event: 21
- Fork event: 1
Last Year
- Issues event: 3
- Watch event: 7
- Issue comment event: 2
- Push event: 13
- Fork event: 1
Committers metadata
Last synced: 16 days ago
Total Commits: 75
Total Committers: 4
Avg Commits per committer: 18.75
Development Distribution Score (DDS): 0.107
Commits in past year: 21
Committers in past year: 1
Avg Commits per committer in past year: 21.0
Development Distribution Score (DDS) in past year: 0.0
| Name | Commits | |
|---|---|---|
| Meng2077 | 9****7 | 67 |
| Tomislav Hengl | t****l@g****m | 5 |
| yu-feng-ho | 1****o | 2 |
| Davide Consoli | d****i@o****g | 1 |
Committer domains:
Issue and Pull Request metadata
Last synced: 3 months ago
Total issues: 1
Total pull requests: 0
Average time to close issues: N/A
Average time to close pull requests: N/A
Total issue authors: 1
Total pull request authors: 0
Average comments per issue: 0.0
Average comments per pull request: 0
Merged pull request: 0
Bot issues: 0
Bot pull requests: 0
Past year issues: 1
Past year pull requests: 0
Past year average time to close issues: N/A
Past year average time to close pull requests: N/A
Past year issue authors: 1
Past year pull request authors: 0
Past year average comments per issue: 0.0
Past year average comments per pull request: 0
Past year merged pull request: 0
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
- Meng2077 (1)
Top Pull Request Authors
Top Issue Labels
Top Pull Request Labels
Score: 4.0943445622221