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Collaborative project: Dynamic agricultural weather indicators for extreme weather prediction in agriculture with methods of artificial intelligence and machine learning (AI/ML) - subproject A (DynAWI)
Project
Project code: 28DK118A20
Contract period: 05.07.2021
- 04.07.2024
Budget: 285,066 Euro
Purpose of research: Applied research
Keywords: AI Artificial Intelligence, crop production, data management, climate (climate relevance, climate protection, climate change), soil (soil conservation, soil fertility, soil cultivation, soil health), remote sensing, forecast
According to the BMEL Arable Farming Strategy 2035, agriculture in Germany faces the challenge of adapting to extreme weather situations (e.g. drought, drought, late frost, heavy rainfall, hail) that have altered because of climate change. The project Dynamic Agricultural Weather Indicators (AWI) for Extreme Weather Forecasts in Agriculture (DynAWI) aims to develop a process chain for spatial data integration and analysis by coupling scalable spatial data infrastructures with methods of artificial intelligence or machine learning (AI/ML). The project is implemented using the example of the extreme weather situations drought/dryness, late frost and soil erosion by water.
Section overview
Subjects
- Crop Production
Framework programme
Funding programme
Excutive institution
Federal Research Centre for Cultivated Plants – Julius Kühn-Institut (JKI)
Funding institution
Project management agencies
Associated projects: DynAWI
- Collaborative project: Dynamic agricultural weather indicators for extreme weather prediction in agriculture with methods of artificial intelligence and machine learning (AI/ML) - subproject B
- Collaborative project: Dynamic agricultural weather indicators for extreme weather prediction in agriculture with methods of artificial intelligence and machine learning (AI/ML) - subproject C
- Collaborative project: Dynamic agricultural weather indicators for extreme weather prediction in agriculture with methods of artificial intelligence and machine learning (AI/ML) - subproject D
- Collaborative project: Dynamic agricultural weather indicators for extreme weather prediction in agriculture with methods of artificial intelligence and machine learning (AI/ML) - subproject E
