About benchmark datasets

Benchmark datasets play a crucial role in the development and evaluation of machine learning models. These datasets provide a standardized set of data that researchers can use to train and test their models, ensuring that comparisons between different models are fair and meaningful. Benchmark datasets are typically well-curated, annotated, and representative of the real-world problems they aim to address. By using benchmark datasets, researchers can objectively measure the performance of their models and identify areas for improvement.

About PANGAEA

PANGAEA is a prominent example of a benchmark dataset in the field of earth observation. It provides a comprehensive collection of geospatial data that researchers can use to test machine learning models for various applications, such as:

• Land cover classification
• Change detection
• Environmental monitoring

PANGAEA is designed as an evaluation protocol that covers a diverse set of datasets, tasks, resolutions, sensor modalities, and temporalities. Additionally, PANGAEA targets benchmarking Geospatial Foundation Models (GFMs), an increasing trend in AI and key strategic capability.