Work

The EuroCropsML time series benchmark dataset for few-shot crop type classification in Europe

Year: 2025

Type: data-paper

Abstract: We introduce EUROCROPSML, an analysis-ready remote sensing dataset based on the open-source EUROCROPS collection, for machine learning (ML) benchmarking of time series crop type classification in Europe. It is the first time-resolved remote sensing dataset designed to benchmark transnational few-shot crop type classification algorithms that supports advancements in algorithmic development and research comparability. It comprises 706683 multi-class labeled data points across 176 crop classes. Each data point features a time series of per-parcel median pixel values extracted from Sentinel-2 L1C data and precise geospatial coordinates. EUROCROPSML is publicly available on Zenodo.

Source: Scientific Data

DOI: 10.1038/s41597-025-04952-7

Authors: Joana Reuss, Jan Macdonald, Simon Becker, Lorenz Richter, Marco Körner

Institutions: Technical University of Munich, ETH Zurich, Zuse Institute Berlin

Language: English

Topic: Remote Sensing in Agriculture

Subfield: Ecology

Field: Environmental Science

Domain: Physical Sciences

SDG: Zero hunger

Open Access status: gold

Estimated APC paid: $2,490