A Deeper Insight into Your Field Today
Conference
Format: CPS Abstract - IAOS 2026
Session: AI & ML in official statistics (3)
Wednesday 13 May 4:30 p.m. - 6 p.m. (Europe/Vilnius)
Abstract
Lithuania was among the first EU member states to initiate the application of a field monitoring system using satellite technology. For several years, the NPA has been utilizing satellite data for land cover monitoring. Leveraging this extensive experience, we have once again taken a leadership role, becoming the first state institution to develop advanced digital tools that allow farmers to remotely monitor agricultural areas and analyze ongoing processes themselves. Most importantly, we have made these tools available for free.
By utilizing the map layers developed by the NPA, farmers will be able to plan their operations more accurately, reduce losses, and make economically sound decisions. It is estimated that these tools will help farmers save up to €100 million per year.
This is particularly relevant in today’s context of climate change, characterized by increasingly frequent natural phenomena that negatively impact yields, as well as market instability and rising prices. Furthermore, it addresses the challenges posed by the CBAM (Carbon Border Adjustment Mechanism) fertilizer tax, which is projected to increase farmers' costs by up to €100 million.
The NPA’s expertise will serve as a cornerstone for a future ambitious project—the European Remote Earth Observation System. Above all, these innovative solutions are designed first and foremost to assist farmers, providing them with comprehensive benefits and support.
12 Digital Tools Developed:
1. Crop quality assessment
2. Identification of crop yield zones and harvest forecasting
3. Crop lodging assessment (evaluation of flattened crops)
4. Soil organic carbon classification
5. Soil moisture and waterlogging classification
6. Identification of areas affected by soil erosion
7. Crop heterogeneity (unevenness) assessment
8. Preliminary crop classification
9. Automated mapping of crop boundaries
10. Automated land cover classification
11. Identification and monitoring of organic farming areas
12. Stubble identification and monitoring