Overview of GeoLifeCLEF 2024: Species Composition Prediction with High Spatial Resolution at Continental Scale using Remote Sensing

Abstract

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.