
Jointly with the European Commission’s JRC, OpenGeoHub is building a web-service with dynamic soil data that can be used to serve the EO soil observatory. JRC’s European Soil Data Center is also behind one of the world’s biggest soil monitoring systems called LUCAS Soil. One of the main objectives of the EO soil observatory is to develop EO-based solutions to help alert countries and individuals independently of the national systems (within weeks since some event such as major flood, erosion etc happens). The system needs are described in detail in “European Soil Data Centre 2.0: Soil data and knowledge in support of the EU policies”.
What is the challenge?
The EU lacks a centralized system for dynamic soil data and real-time alerts, which hinders coordinated soil monitoring and response efforts. Automated updates and targeted notifications, such as alerts for soil quality changes, are currently missing from the European Soil Observatory.
Our solution
This use case proposes a web-based service that integrates satellite-derived soil data with automated alert systems. The platform will send real-time updates via email and social media, making soil health information more accessible and actionable for EU stakeholders.

Who will benefit?
European policymakers, environmental agencies, and agricultural stakeholders will benefit by receiving timely updates on soil conditions to support sustainable land use practices.



Scope
Target Partner Organizations
OEMC Leading Partner
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Type of output
Web-service, email alerts
Technology readiness level
TRL3: Experimental proof of concept
Location
Europe
Related Publications
Links of interest
- Xuemeng Tian: Spatiotemporal prediction of SOCD for Europe (2000-2022) in 3D+T
- Tom Hengl: The 7 step framework for soil health assessment in an autonomous GIS infrastructure
- Time-series of Landsat-based bi-monthly and annual spectral indices for continental Europe for 2000–2022
- Spatiotemporal prediction of soil organic carbon density for Europe (2000--2022) in 3D+T based on Landsat-based spectral indices time-series