English

The GeoLifeCLEF 2020 Dataset

Computer Vision and Pattern Recognition 2020-04-10 v1 Machine Learning Machine Learning

Abstract

Understanding the geographic distribution of species is a key concern in conservation. By pairing species occurrences with environmental features, researchers can model the relationship between an environment and the species which may be found there. To facilitate research in this area, we present the GeoLifeCLEF 2020 dataset, which consists of 1.9 million species observations paired with high-resolution remote sensing imagery, land cover data, and altitude, in addition to traditional low-resolution climate and soil variables. We also discuss the GeoLifeCLEF 2020 competition, which aims to use this dataset to advance the state-of-the-art in location-based species recommendation.

Cite

@article{arxiv.2004.04192,
  title  = {The GeoLifeCLEF 2020 Dataset},
  author = {Elijah Cole and Benjamin Deneu and Titouan Lorieul and Maximilien Servajean and Christophe Botella and Dan Morris and Nebojsa Jojic and Pierre Bonnet and Alexis Joly},
  journal= {arXiv preprint arXiv:2004.04192},
  year   = {2020}
}

Comments

10 pages, 4 figures

R2 v1 2026-06-23T14:44:44.143Z