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Spatial Dataset of Climate Robust and High-Yield Agricultural Areas in Brandenburg: Results of a Classification Framework Using Bio-Economic Climate Simulations
by
von Czettritz, Hannah Jona
, Zander, Peter
, Uthes, Sandra
, Kersebaum, Kurt-Christian
, Schuler, Johannes
in
Agricultural land
/ Agricultural production
/ Agricultural productivity
/ Arable land
/ bio-economic analysis
/ Brandenburg
/ Classification
/ Climate change
/ climate resilient agriculture
/ Climatic changes
/ Crops
/ Datasets
/ Decision making
/ Decisions
/ Drought
/ Droughts
/ Environmental aspects
/ Farms
/ Food supply
/ Geospatial data
/ Germany
/ Growth models
/ Land use
/ land use conflicts
/ Land use management
/ Natural resources
/ peatland conservation
/ Planning
/ Power plants
/ Regional planning
/ Renewable resources
/ Robustness
/ Simulation
/ Simulation methods
/ Soil erosion
/ Spatial data
/ spatial planning
/ Water shortages
/ Wheat
/ Wind erosion
2025
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Spatial Dataset of Climate Robust and High-Yield Agricultural Areas in Brandenburg: Results of a Classification Framework Using Bio-Economic Climate Simulations
by
von Czettritz, Hannah Jona
, Zander, Peter
, Uthes, Sandra
, Kersebaum, Kurt-Christian
, Schuler, Johannes
in
Agricultural land
/ Agricultural production
/ Agricultural productivity
/ Arable land
/ bio-economic analysis
/ Brandenburg
/ Classification
/ Climate change
/ climate resilient agriculture
/ Climatic changes
/ Crops
/ Datasets
/ Decision making
/ Decisions
/ Drought
/ Droughts
/ Environmental aspects
/ Farms
/ Food supply
/ Geospatial data
/ Germany
/ Growth models
/ Land use
/ land use conflicts
/ Land use management
/ Natural resources
/ peatland conservation
/ Planning
/ Power plants
/ Regional planning
/ Renewable resources
/ Robustness
/ Simulation
/ Simulation methods
/ Soil erosion
/ Spatial data
/ spatial planning
/ Water shortages
/ Wheat
/ Wind erosion
2025
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Do you wish to request the book?
Spatial Dataset of Climate Robust and High-Yield Agricultural Areas in Brandenburg: Results of a Classification Framework Using Bio-Economic Climate Simulations
by
von Czettritz, Hannah Jona
, Zander, Peter
, Uthes, Sandra
, Kersebaum, Kurt-Christian
, Schuler, Johannes
in
Agricultural land
/ Agricultural production
/ Agricultural productivity
/ Arable land
/ bio-economic analysis
/ Brandenburg
/ Classification
/ Climate change
/ climate resilient agriculture
/ Climatic changes
/ Crops
/ Datasets
/ Decision making
/ Decisions
/ Drought
/ Droughts
/ Environmental aspects
/ Farms
/ Food supply
/ Geospatial data
/ Germany
/ Growth models
/ Land use
/ land use conflicts
/ Land use management
/ Natural resources
/ peatland conservation
/ Planning
/ Power plants
/ Regional planning
/ Renewable resources
/ Robustness
/ Simulation
/ Simulation methods
/ Soil erosion
/ Spatial data
/ spatial planning
/ Water shortages
/ Wheat
/ Wind erosion
2025
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Spatial Dataset of Climate Robust and High-Yield Agricultural Areas in Brandenburg: Results of a Classification Framework Using Bio-Economic Climate Simulations
Journal Article
Spatial Dataset of Climate Robust and High-Yield Agricultural Areas in Brandenburg: Results of a Classification Framework Using Bio-Economic Climate Simulations
2025
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Overview
Coherent spatial data are crucial for informed land use and regional planning decisions, particularly in the context of securing a crisis-proof food supply and adapting to climate change. This dataset provides spatial information on climate-robust and high-yield agricultural arable land in Brandenburg, Germany, based on the results of a classification using bio-economic climate simulations. The dataset is intended to support regional planning and policy makers in zoning decisions (e.g., photovoltaic power plants) by identifying climate-robust arable land with high current and stable future production potential that should be reserved for agricultural use. The classification method used to generate the dataset includes a wide range of indicators, including established approaches, such as a soil quality index, drought, water, and wind erosion risk, as well as a dynamic approach, using bio-economic simulations, which determine the production potential under future climate scenarios. The dataset is a valuable resource for spatial planning and climate change adaptation, contributing to long-term food security especially in dry areas such as the state of Brandenburg facing increased production risk under future climatic conditions, thereby serving globally as an example for land use planning challenges related to climate change.
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