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EuroCropsML: A Time Series Benchmark Dataset For Few-Shot Crop Type Classification

Year: 2024

Type: preprint

Abstract: We introduce EuroCropsML, an analysis-ready remote sensing machine learning dataset for time series crop type classification of agricultural parcels in Europe. It is the first dataset designed to benchmark transnational few-shot crop type classification algorithms that supports advancements in algorithmic development and research comparability. It comprises 706 683 multi-class labeled data points across 176 classes, featuring annual time series of per-parcel median pixel values from Sentinel-2 L1C data for 2021, along with crop type labels and spatial coordinates. Based on the open-source EuroCrops collection, EuroCropsML is publicly available on Zenodo.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2407.17458

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

Language: English

Topic: Remote Sensing in Agriculture

Subfield: Ecology

Field: Environmental Science

Domain: Physical Sciences

SDG: Zero hunger

Open Access status: green

OpenAlex ID: W6966746504

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