The GeoLifeCLEF 2020 Dataset

Elijah Cole (1) , Benjamin Deneu (2) , Titouan Lorieul (2) , Maximilien Servajean (3) , Christophe Botella (4) , Dan Morris (5) , Nebojsa Jojic (5) , Pierre Bonnet (6) , Alexis Joly (2)

1 CALTECH - California Institute of Technology
2 ZENITH - Scientific Data Management
3 ADVANSE - ADVanced Analytics for data SciencE
4 LECA - Laboratoire d'Ecologie Alpine
5 Microsoft Research [Redmond]
6 UMR AMAP - Botanique et Modélisation de l'Architecture des Plantes et des Végétations

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.

Domaines: Intelligence artificielle [cs.AI]; Vision par ordinateur et reconnaissance de formes [cs.CV]; Multimédia [cs.MM]; Apprentissage [cs.LG]; Modélisation et simulation; Biodiversité et Ecologie; Environnement et Société

Elijah Cole, Benjamin Deneu, Titouan Lorieul, Maximilien Servajean, Christophe Botella, et al.. The GeoLifeCLEF 2020 Dataset. 2020. ⟨hal-02989062⟩