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Overview of GeoLifeCLEF 2024: Species composition prediction with high spatial resolution at continental scale using remote sensing

Picek Lukáš, Botella Christophe, Servajean Maximilien, Leblanc César, Palard Rémi, Larcher Théo, Deneu Benjamin, Marcos Diego, Estopinan Joaquim, Bonnet Pierre, Joly Alexis. 2024. Overview of GeoLifeCLEF 2024: Species composition prediction with high spatial resolution at continental scale using remote sensing. In : Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2024). Faggioli Guglielmo (ed.), Ferro Nicola (ed.), Galuščáková Petra (ed.), García Seco de Herrera Alba (ed.). Aachen : CEUR-WS, 1966-1977. (CEUR Workshop Proceedings, 3740) Conference and Labs of the Evaluation Forum (CLEF 2024), Grenoble, France, 9 Septembre 2024/12 Septembre 2024.

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Résumé : Understanding the spatiotemporal distribution of species is a cornerstone of ecology and conservation. Pairing species observations with geographic and environmental predictors allows us to model the relationship between an environment and the species present at a given location. In light of that, we organize an annual competition, GeoLifeCLEF, which focuses on benchmarking and advancing state-of-the-art species distribution modeling using available bioclimatic and remote sensing data. The GeoLifeCLEF 2024 dataset spans across Europe and encompasses most of its flora. The species observation data comprises over 5 million Presence-Only (PO) occurrences and approximately 90 thousand Presence-Absence (PA) surveys. Those data are paired with various high-resolution rasters, including remote sensing imagery, land cover, and elevation, and are combined with coarse-resolution data such as climate, soil, and human footprint variables. In this paper, we present (i) an overview of the GeoLifeCLEF 2024 competition, (ii) a description of the provided data, (iii) an overview of approaches used by the participating teams, and (iv) the main results analysis.

Mots-clés libres : LifeCLEF, Biodiversity, Environmental data, Species distribution, Prediction, Evaluation, Benchmark, Methods comparison, Presence-only data, Presence-absence, Model performance, Remote Sensing

Agences de financement européennes : European Commission

Programme de financement européen : Horizon Europe

Projets sur financement : (EU) Modern Approaches to the Monitoring of BiOdiversity, (EU) safeGUARDing biodivErsity aNd critical ecosystem services across sectors and scales

Auteurs et affiliations

  • Picek Lukáš, INRIA (FRA)
  • Botella Christophe, INRIA (FRA)
  • Servajean Maximilien, CNRS (FRA)
  • Leblanc César, CIRAD-BIOS-UMR AMAP (FRA)
  • Palard Rémi, CIRAD-BIOS-UMR AMAP (FRA)
  • Larcher Théo, INRIA (FRA)
  • Deneu Benjamin, CIRAD-BIOS-UMR AMAP (FRA)
  • Marcos Diego, INRIA (FRA)
  • Estopinan Joaquim, INRIA (FRA)
  • Bonnet Pierre, CIRAD-BIOS-UMR AMAP (FRA) ORCID: 0000-0002-2828-4389
  • Joly Alexis, INRIA (FRA)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/613023/)

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