mlsanityData to 7 Oct 2026

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

arXiv 2407.17458 ↗First posted 24 Jul 2024cs.LGcited by 11

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Abstract (arXiv)

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.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 6 of its 27 references that are in the map. First posted on arXiv 24 Jul 2024.

Builds on

6 of 27 references.

References · 6

  1. 2017Attention Is All You Needcited by 59,932
  2. 2021Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networkscited by 141
  3. 2021Crop mapping from image time series: deep learning with multi-scale label hierarchiescited by 42
  4. 2019BreizhCrops: A Time Series Dataset for Crop Type Mappingcited by 34
  5. 2023There Are No Data Like More Data- Datasets for Deep Learning in Earth Observationcited by 16
  6. 2021EuroCrops: A Pan-European Dataset for Time Series Crop Type Classificationcited by 13

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 5; 2026: 6.

11 papers.

  1. 2025GTPBD: A Fine-Grained Global Terraced Parcel and Boundary Datasetcited by 3
  2. 2025A Comprehensive Review of Agricultural Parcel and Boundary Delineation from Remote Sensing Images: Recent Progress and Future Perspectivescited by 3
  3. 2026SwissCrop25: A National Multi-Year Benchmark for Operational Crop Mappingcited by 3
  4. 2026Benchmarking Geospatial Foundation Models for Agriculture Applicationscited by 2
  5. 2025Benchmarking for Practice: Few-Shot Time-Series Crop-Type Classification on the EuroCropsML Datasetcited by 1
  6. 2025T3S: Think in Thermal Time for Generalizable Crop Mapping from Satellite Image Time Seriescited by 0
  7. 2025Farm-Level, In-Season Crop Identification for Indiacited by 0
  8. 2026The Normalized Difference Layer: A Differentiable Spectral Index Formulation for Deep Learningcited by 0
  9. 2026Retrieval-Augmented Multi-scale Framework for County-Level Crop Yield Prediction Across Large Regionscited by 0
  10. 2026DirPA: Addressing Prior Shift in Imbalanced Few-shot Crop-type Classificationcited by 0
  11. 2026TIDES: Implicit Time-Awareness in Selective State Space Modelscited by 0