Crop Supply Response Functions at Field Level in Germany Using Satellite Data

This is a presentation of the current work on crop supply response functions at field level in Germany using satellite data. This is also ongoing work. Description: Field-Level Crop Supply Response in German Winter Wheat–Rapeseed Rotations Current national agricultural models estimate crop acreage responses at the regional scale, which obscures the field-level decisions that actually drive land use change. This aggregation oversimplifies how farmers respond to price signals, ignoring rotation constraints, soil quality, topography, and weather uncertainty. This research addresses that gap by developing field-level supply response functions for German winter wheat–winter rapeseed rotations, incorporating biophysical heterogeneity, input cost dynamics, and stochastic weather effects. The analytical database draws on four variable groups: spatial identifiers, land use outcomes (binary indicators for crop types), expected farm gate prices constructed from market quotations during the sowing window, and weather and soil characteristics. Land use data comes from a satellite-derived dataset (Tetteh et al., 2025) integrating Sentinel-1, Sentinel-2, and Landsat imagery for 2017–2023. Climate variables are sourced from the German Weather Service (DWD), while soil data comes from the BGR soil map. The core methodological tool is a Markov Transition Model, estimated across two decision margins. The rotational margin captures switching probabilities between wheat and rapeseed within a rotation, while the extensive margin estimates the likelihood of a field exiting the rotation entirely to alternative crops. Transition probability matrices are used to compute expected crop choices conditional on the prior year's planting decision. While the dataset is still being finalized, anticipated findings point to strong rotational inertia, with measurable switching probabilities that respond to relative price movements, fertilizer costs, and precipitation patterns. These results have direct implications for the BrightSpace ex ante impact assessment framework, specifically Pillar II. Replacing regional aggregate elasticities with field-level transition probabilities would enable more realistic simulations of policy changes — such as CAP reforms — by capturing rotation-specific inertia, soil heterogeneity, and weather-driven variability across both short- and long-run adjustment horizons. Funding acknowledgement Funded by the European Union. Grant Agreement No. 101060075. Views and opinions expressed are those of the authors only and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the granting authority can be held responsible for them. Legal notice This document was produced under the terms and conditions of Grant Agreement No. 101060075 for the European Commission. It does not necessary reflect the view of the European Union and in no way anticipates the Commission’s future policy in this area. The European Commission is not liable for any consequence stemming from the reuse of this publication. © BrightSpace, 2026 The reuse of this document is authorised under a Creative Commons Attribution 4.0 International (CCBY 4.0) licence (https://creativecommons.org/licenses/by/4.0/). This means that reuse is allowed provided appropriate credit is given and any changes are indicated. For any use or reproduction of elements that are not owned by the BrightSpace consortium, permission may need to be sought directly from the respective right holders. Project information BrightSpace Horizon Europe project Grant Agreement No. 101060075 https://cordis.europa.eu/project/id/101060075 CALL: Innovative governance, environmental observations and digital solutions in support of the Green Deal WORK PROGRAMME Topic ID: HORIZON-CL6-2021-GOVERNANCE-01-12 EU agriculture within a safe and just operating space and planetary boundaries BrightSpace Project coordination: Wageningen Economic Research, The Hague, NL Contact: brightspace.wser@wur.nl | Website: www.brightspace-project.eu Project duration: 1 November 2022 – 31 October 2027