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ZALFHomeStructureResearch Area 4 "Simulation and Data Science"Landscape Modelling

Landscape Modeling

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This working group develops the framework for the coupling of fundamentally different modelling approaches into an integrate landscape simulation. Initially, the working group will concentrate on a concept for the integration of process-based simulation models for cropland, grassland and forest ecosystems into a single modelling framework, with a special focus on transition zones between these ecosystems and the observed abiotic processes in these transition zones. In addition, remote sensing data is to be used to parameterise, initialise and drive one-dimensional process-based and other types of two- to three-dimensional models at the landscape scale. This includes models for socioeconomic processes.

 

 

Publications WG
MyTitle: To enhance sustainable development goal research, open up commercial satellite image archives
MyLinkAnsehenUrl: https://doi.org/10.1073/pnas.2410246122, Resolve DOI name
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MyAutoren: Rufin, P., Meyfroidt, P., Akinyemi, F. O., Estes, L., Ibrahim, E. S., Jain, M., Kerner, H., Lisboa, S. N., Lobell, D., Nakalembe, C., Persello, C., Picoli, M. C. A., Ribeiro, N., Sitoe, A. A., Waha, K., Wang, S. (2025)
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To enhance sustainable development goal research, open up commercial satellite image archives

Rufin, P., Meyfroidt, P., Akinyemi, F. O., Estes, L., Ibrahim, E. S., Jain, M., Kerner, H., Lisboa, S. N., Lobell, D., Nakalembe, C., Persello, C., Picoli, M. C. A., Ribeiro, N., Sitoe, A. A., Waha, K., Wang, S. (2025)
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MyTitle: Winter wheat–soybean relay intercropping in conjunction with a shift in sowing dates as a climate change adaptation and mitigation strategy for crop production in Germany
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MyLinkPDFUrl: http://dx.doi.org/10.1016/j.fcr.2024.109695, Resolve DOI name
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MyAutoren: Yu, J., Eyshi Rezaei, E., Reckling, M., Nendel, C. (2025)
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Winter wheat–soybean relay intercropping in conjunction with a shift in sowing dates as a climate change adaptation and mitigation strategy for crop production in Germany

Yu, J., Eyshi Rezaei, E., Reckling, M., Nendel, C. (2025)
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MyTitle: Ten deep learning techniques to address small data problems with remote sensing
MyLinkAnsehenUrl: http://dx.doi.org/10.1016/j.jag.2023.103569, Resolve DOI name
MyLinkPDFUrl: https://publications.zalf.de/publications/98E8D5F1-F66D-491F-BAF2-0D696C65D525-1.pdf, PDF take a look / download
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MyAutoren: Safonova, A., Ghazaryan, G., Stiller, S., Main-Knorn, M., Nendel, C., Ryo, M. (2023)
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Ten deep learning techniques to address small data problems with remote sensing

Safonova, A., Ghazaryan, G., Stiller, S., Main-Knorn, M., Nendel, C., Ryo, M. (2023)
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Projects WG
MyTitle: ModOKlim: Model-based scenario analysis to optimise plant production for climate protection
MyLinkAnsehenUrl: https://www.zalf.de/en/forschung_lehre/projekte/Pages/details.aspx?iddp=2397, Resolve DOI name
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MyTitelMehrzeilig:
MyTextfeld: Period: 01.11.2023
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ModOKlim: Model-based scenario analysis to optimise plant production for climate protection

Period: 01.11.2023
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MyTitle: Clim4Cast - Central European alliance for increasing climate change resilience to combined consequences of drought, heatwave, and fire weather through regionally-tuned forecasting
MyLinkAnsehenUrl: https://www.zalf.de/en/forschung_lehre/projekte/Pages/details.aspx?iddp=2368, Take a look
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MyTitelMehrzeilig:
MyTextfeld: Start: 01.03.2023
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Clim4Cast - Central European alliance for increasing climate change resilience to combined consequences of drought, heatwave, and fire weather through regionally-tuned forecasting

Start: 01.03.2023
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MyTitle: YieldGEM – Improving large-area mechanistic yield simulations through disentangling genotype × environment × management factors
MyLinkAnsehenUrl: https://www.zalf.de/en/forschung_lehre/projekte/Pages/details.aspx?iddp=2365, Take a look
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MyTextfeld: Start: 01.03.2023
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YieldGEM – Improving large-area mechanistic yield simulations through disentangling genotype × environment × management factors

Start: 01.03.2023
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MyTitle: MoorgrünFE: Use of proximal and remote sensing data from various sensors to develop modeling approaches for assessing soil organic carbon (SOC) stocks and its dynamics on agriculturally used grasslands on peat soils
MyLinkAnsehenUrl: https://www.zalf.de/en/forschung_lehre/projekte/Pages/details.aspx?iddp=2331, Take a look
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MyTitelMehrzeilig:
MyTextfeld: Start: 01.11.2022
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MoorgrünFE: Use of proximal and remote sensing data from various sensors to develop modeling approaches for assessing soil organic carbon (SOC) stocks and its dynamics on agriculturally used grasslands on peat soils

Start: 01.11.2022
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MyTitle: KIKompAG - Multi-modal data integration, domain-specific methods and AI to strengthen data literacy in agricultural research
MyLinkAnsehenUrl: https://www.zalf.de/en/forschung_lehre/projekte/Pages/details.aspx?iddp=2329, Take a look
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MyTitelMehrzeilig:
MyTextfeld: Start 01.10.2022
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KIKompAG - Multi-modal data integration, domain-specific methods and AI to strengthen data literacy in agricultural research

Start 01.10.2022
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Contact

 

Head of working group

Prof. Dr. Claas Nendel
T +49 (0)33432 82-355

 

Address

Leibniz-Zentrum für
Agrarlandschaftsforschung (ZALF) e. V.
Eberswalder Straße 84
15374 Müncheberg​​

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