EuroCropsML¶
Ready-to-use benchmark dataset for few-shot crop type classification using Sentinel-2 imagery.
Release v0.1.0
EuroCropsML is a pre-processed and ready-to-use machine learning dataset for crop type classification of agricultural parcels in Europe. It consists of a total of 706,683 multi-class labeled data points with a total of 176 distinct classes. Each data point contains an annual time series of per parcel median pixel values of Sentinel-2 L1C reflectance data for the year 2021. The dataset is based on Version 9 of EuroCrops, an open-source collection of remote sensing reference data.
For EuroCropsML we acquired and aggregated data for the following countries:
Country |
Total number of datapoints |
Number of distinct classes |
|---|---|---|
Estonia |
175,906 |
127 |
Latvia |
431,143 |
103 |
Portugal |
99,634 |
79 |
|
|
|---|
The distribution of class labels differs substantially between the regions of Estonia, Latvia, and Portugal. This makes transferring knowledge gained in one region to another region quite challenging, especially if only few labeled data points are available. Therefore, this dataset is particularly suited to explore transfer-learning methods for few-shot crop type classification.
The data acquisition, aggregation, and pre-processing steps are schematically illustrated below. A more detailed description is given in the dataset section of our documentation.
Table of Contents¶
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