A crop sequence dataset of the German federal state of North Rhine-Westphalia from 2019-2024

Area of Science:

• Agricultural Science
• Geographic Information Systems (GIS)
• Environmental Science

Background:

• Tracking crop sequences over time is difficult due to changing field boundaries.
• Existing methods using field identifiers have low matching rates.
• Agricultural subsidy records provide annual crop data but lack temporal continuity at the parcel level.

Purpose of the Study:

• To create a comprehensive dataset of crop sequences for agricultural fields in North Rhine-Westphalia (2019-2024).
• To develop and validate a novel spatial joining approach for accurate crop sequence tracking.
• To provide an open-source tool to facilitate agricultural and environmental research.

Main Methods:

• Utilized vector data of agricultural land and field parcels (GeoParquet, WGS84).
• Developed a novel spatial joining approach based on the largest area overlap between consecutive years to link field parcels.
• Sourced underlying crop type data from the OpenGeodata portal of North Rhine-Westphalia.

Main Results:

• Generated a dataset covering approximately 1.44 million hectares and 740,731 field parcels.
• Achieved a 97% matching rate for crop sequences at the field level, significantly outperforming previous methods (24%).
• Developed and released an open-source Python package for applying the methodology.

Conclusions:

• The novel spatial joining approach effectively overcomes challenges in tracking crop sequences despite changing field boundaries.
• The comprehensive dataset and methodology support detailed analyses of agricultural practices, environmental impacts, and policy assessments.
• The approach is transferable to other regions with available Integrated Administration and Control System (IACS) data.