EuroCrops: A Pan-European Dataset for Time Series Crop Type Classification

TL;DR

EuroCrops is a comprehensive European dataset with self-declared crop field annotations, designed to advance land cover classification research and address transnational data challenges in remote sensing.

Contribution

The paper introduces EuroCrops, a new dataset with a harmonized taxonomy and multi-format releases, facilitating cross-border crop classification research.

Findings

Dataset includes diverse European crop data from all EU countries.

Introduces HCAT-ID taxonomy for consistent reference data.

Highlights challenges of transnational remote sensing data integration.

Abstract

We present EuroCrops, a dataset based on self-declared field annotations for training and evaluating methods for crop type classification and mapping, together with its process of acquisition and harmonisation. By this, we aim to enrich the research efforts and discussion for data-driven land cover classification via Earth observation and remote sensing. Additionally, through inclusion of self-declarations gathered in the scope of subsidy control from all countries of the European Union (EU), this dataset highlights the difficulties and pitfalls one comes across when operating on a transnational level. We, therefore, also introduce a new taxonomy scheme, HCAT-ID, that aspires to capture all the aspects of reference data originating from administrative and agency databases. To address researchers from both the remote sensing and the computer vision and machine learning communities, we publish the dataset in different formats and processing levels.