Overview of GeoLifeCLEF 2022: Predicting species presence from multi-modal remote sensing, bioclimatic and pedologic data

Lorieul Titouan, Cole Elijah, Deneu Benjamin, Servajean Maximilien, Bonnet Pierre, Joly Alexis. 2022. Overview of GeoLifeCLEF 2022: Predicting species presence from multi-modal remote sensing, bioclimatic and pedologic data. In : Proceedings of the Working Notes of CLEF 2022 - Conference and Labs of the Evaluation Forum. Faggioli Guglielmo (ed.), Ferro Nicola (ed.), Hanbury Allan (ed.), Potthast Martin (ed.). Aachen : CEUR-WS, 1940-1956. (CEUR Workshop Proceedings, 3180) Conference and Labs of the Evaluation Forum (CLEF 2022), Bologne, Italie, 5 Septembre 2022/8 Septembre 2022.

Résumé : 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 advance research in this area, a large-scale machine learning competition called GeoLifeCLEF 2022 was organized. It relied on a dataset of 1.6 million observations from 17K species of animals and plants. These observations were paired with high-resolution remote sensing imagery, land cover data, and altitude, in addition to traditional lowresolution climate and soil variables. The main goal of the challenge was to better understand how to leverage remote sensing data to predict the presence of species at a given location. This paper presents an overview of the competition, synthesizes the approaches used by the participating groups, and analyzes the main results. In particular, we highlight the ability of remote sensing imagery and convolutional neural networks to improve predictive performance, complementary to traditional approaches.

Mots-clés libres : LifeCLEF, Evaluation, Benchmark, Biodiversity, Presence-only data, Environmental data, Remote sensing imagery, Multi-modal data, Species distribution, Species distribution models

Auteurs et affiliations

• Lorieul Titouan, INRIA (FRA)
• Cole Elijah, Caltech (USA)
• Deneu Benjamin, INRIA (FRA)
• Servajean Maximilien, CNRS (FRA)
• Bonnet Pierre, CIRAD-BIOS-UMR AMAP (FRA) ORCID: 0000-0002-2828-4389
• Joly Alexis, INRIA (FRA)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/611523/)

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